Search for: All records

ABSTRACT In topology optimization of compliant mechanisms, the specific placement of boundary conditions strongly affects the resulting material distribution and performance of the design. At the same time, the most effective locations of the loads and supports are often difficult to find manually. This substantially limits topology optimization's effectiveness for many mechanism design problems. We remove this limitation by developing a method which automatically determines optimal positioning of a prescribed input displacement and a set of supports simultaneously with an optimal material layout. Using nonlinear elastic physics, we synthesize a variety of compliant mechanisms with large output displacements, snap‐through responses, and prescribed output paths, producing designs with significantly improved performance in every case tested. Compared to optimal designs generated using manually designed boundary conditions used in previous studies, the mechanisms presented in this paper see performance increases ranging from 47% to 380%. The results show that nonlinear mechanism responses may be particularly sensitive to boundary condition locations and that effective placements can be difficult to find without an automated method. 

The invention of the wheel is widely credited as a pivotal moment in human history, yet the details surrounding its discovery are shrouded in mystery. There remains no scholarly consensus on key questions such as where, how and by whom this technology was originally invented. In this study, we employ state-of-the-art techniques from computational structural mechanics to shed light on this long-standing puzzle. Based on this analysis, we propose a probable path along which the wheel evolved via a sequence of three major innovations. We also introduce an original computational design algorithm that autonomously generates a wheel-and-axle system using an evolutionary process that offers insight into the way in which the first wheels likely evolved nearly 6000 years ago. Our analysis provides new supporting evidence for the recently advanced theory that the wheel was invented by Neolithic miners harvesting copper ore from the Carpathian Mountains as early as 3900 BC. Moreover, we show how the discovery of the wheel was made possible by the unique physical features of the mine environment, whose impact was analogous to the selective environmental pressures that drive biological evolution. 

In current engineering practice, computer-aided design (CAD) tools play a key role in the design and fabrication of most mechanical systems, including the design of most vehicles. This software tends to rely heavily on human designers to provide the basic design concept, with the software being used to computationally render an existing design, or to perform modifications to a design to achieve incremental improvements in performance. However, an emerging class of computational methods, known astopology optimizationmethods, offers the potential for trueblack boxcomputational design. Under this general framework, practitioners provide the algorithm with the constitutive properties of the design materials, and the mechanical function being designed for (e.g. maximum stiffness under a given loading condition), and the algorithm autonomously generates a description of the corresponding structure. With some exceptions, existing topology optimization methods are limited to generating static, single-body designs. In this study, we present a novel method that builds upon the current state of the art by combining multiple collocated planar design domains to achieve automated computational synthesis of multi-body wheeled vehicles. This capability represents an important step on the path toward automated computational design of increasingly complex, innovative and impactful mechanical systems. 

This work presents a new method for efficiently designing loads and supports simultaneously with material distribution in density-based topology optimization. We use a higher-order or super-Gaussian function to parameterize the shapes, locations, and orientations of mechanical loads and supports. With a distance function as an input, the super-Gaussian function projects smooth geometric shapes which can be used to model various types of boundary conditions using minimal numbers of additional design variables. As examples, we use the proposed formulation to model both concentrated and distributed loads and supports. We also model movable non-design regions of predetermined solid shapes using the same distance functions and design variables as the variable boundary conditions. Computing the design sensitivities using the adjoint sensitivity analysis method, we implement the technique in a 2D topology optimization algorithm with linear elasticity and demonstrate the improvements that the super-Gaussian projection method makes to some common benchmark problems. By allowing the optimizer to move the loads and supports throughout the design domain, the method produces significant enhancements to structures such as compliant mechanisms where the locations of the input load and fixed supports have a large effect on the magnitude of the output displacements.