Topology optimisation for energy management in underwater sensor networks Devesh K. Jhaa, Thomas A. Wettergrenb, Asok Raya,∗ and Kushal Mukherjeec Department of Mechanical & Nuclear Engineering, Pennsylvania State University, University Park, PA 16802-1412, USA; Naval Undersea Warfare Center, Newport, RI 02841-1708, USA and Department of Mechanical & Nuclear Engineering, Pennsylvania State Univ...

1. Abstract In traditional structural topology optimization (TO), the material properties of continuum finite elements of fixed form and coupling are varied to find the optimal topology that satisfies the design problem. We develop an alternative, fundamental formulation where the design space search is dependent on the coupling, and the goal of the topology optimization by penalty (TOP) method...

This paper presents a formulation of robust topology optimization of trusses subjected to the stress constraints under the load uncertainty. A design-dependent uncertainty model of external loads is proposed for considering the variation of truss topology in the course of optimization. For a truss with the discrete member cross-sectional areas, it is shown that the robust topology optimization ...

Hefftner, White, Alpert, and others observed a connection between topology and certain block designs with parameters k = 3 and ,I= 2. In this paper the connection is extended to include all values of I.. The topology is also exploited further to produce some new invariants of designs. The topology also gives an upper bound for the order of the automorphism group of the designs studied which lea...

Generative modeling techniques are being rapidly developed in the field of deep learning, and they have been applied to topology optimization. The variational autoencoder (VAE) is a generative modeling technology that extends the autoencoder to generate new images with a limited latent space. We modified the basic VAE structure to encode optimization conditions and decode latent variables for t...