Combining Structural Topology Optimization and Big Area Additive Manufacturing – A Case Study

Nik Nikolov is an Assistant Professor of Art, Architecture and Design at Lehigh University.

This research project investigated the problems, workflow, and feasibility of designing a small topologically optimized structure and its fabrication in polymer-extruding large area 3d printer. Topology optimization (TO) as an architectural design tool is largely unexplored, in contrast to its wide use in the field of mechanical engineering. As big area additive manufacturing (BAAM) finally enters the realm of full-scale single-build structural design, research like the one proposed holds a significant potential for design innovation in addressing structural expression in buildings of varying scales.

The work was presented at the ACSA Fall Conference: Between the Autonomous & Contingent Object, October 8-10, 2015 at Syracuse University, Syracuse, NY and was accepted for journal publication and presentation at the 2016 International Conference on Structures and Architecture June 19-21, Guimaraes, Portugal. Additionally the work was part of a NSF grant application (Directorate of Engineering, PD 15-1637, proposal title “Development of Binder Jet 3D Printing of Concrete Components for Structural and Architectural Applications”) with prof Clay Naito, co PI.


Using computation to understand noise production and reduction

Justin Jaworski and Keith Moored are Co-PIs and both Assistant Professors of Mechanical Engineering and Mechanics at Lehigh University. They were assisted by graduate student Nathan Wagenhoffer. Below they discusses their research on  how noise is created. 

Aerodynamic noise generation is important to many engineering applications, such as wind turbines and aircraft, where noise annoyance to the public is critical.  Excessive noise explains in part why most airports are located well outside of city limits and major highways are flanked by traffic noise barriers; people don’t like noise. The generation of noise is found by analyzing how the air or fluid around objects is disturbed. For our purposes, we identify noise generation in two broad senses: scattered noise and radiated noise. Scattered noise results from a sound wave encounters a solid body and is amplified and bounces off. Radiated noise is made by vibratory motion of the body. If we can find a way to model acoustic disturbances in air, for example, then we can find how these motions can generate noise.  In a concerted effort to identify the noise from arbitrary solid bodies, we have developed a two-dimensional (2D) acoustic field solver. The 2D model allows us to simplify problems to their essentials, while still ascertaining where and how the noise is generated for a specific body. We simply need to define how does the pressure around a body behaves and then a resulting acoustic field can be found.

But finding the pressure field around an airfoil, for instance, is not a straightforward task. To accurately find the pressure on a moving airfoil, one actually has to solve the equations of fluid flow for the body. We choose to describe our fluids problem with the similar mathematical treatment as the acoustics section. This allows for us to use the same to perform the analysis on the exact same geometry and exploit any speed up algorithms on both problems.   The fluid solver finds how the airfoil makes vorticity, or local spinning of a region of fluid, due to its movement. Vorticity is responsible for most sound generated created at low speeds, so a coupling of this flow solver with the acoustic solver is natural. The motion of a vortex, a coherent region of vorticity, produces a greater pressure than its surrounding area.
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