This Faculty Early Career Development (CAREER) award supports fundamental research to formulate the first topology optimization frameworks that will systematically tailor freeform computational design to manufacture by a specific digital fabrication technology. The research will focus on fabrication technologies based on material extrusion-type Additive Manufacturing (AM), which is used in a wide range of 3D printing technologies at various scales. Topology optimization is a freeform design technique that generates new, high-performing design solutions. Topology optimization is often suggested as a powerful design-for-AM approach because it does not require a pre-conceived idea of the final design layout. However, most topology-optimized designs must be “interpreted†or prepared by the design engineer to facilitate manufacture, a process that may result in performance loss of the final product. This research will develop original topology optimization frameworks that leverage the possibilities and constraints offered by extrusion-type AM processes. The integration of design and manufacture investigated in this project will ease the process used by design engineers and improve the performance of the final fabricated product. Equally important for the project is the integrated educational program that will inspire and train the next generations of design engineers to creatively approach design problems while considering manufacturing aspects. The educational program will stimulate interest in futures in engineering design, especially among students who do not typically engage with the topic.
The overarching goal of this project is the discovery of a new design-fabrication paradigm that shifts design and manufacture from being two separate entities into a single unified process, where the preparation for fabrication step is eliminated. This objective will be achieved through the formulation of novel topology optimization algorithms that leverage the possibilities and constraints associated with extrusion-type AM. The constraints will be formulated implicitly as new manufacturing primitives that mimic the manufacturing process. The design algorithms will consider the fundamental extrusion characteristics and constraints, including: (i) discrete size of the extruding nozzle, (ii) bond quality between adjacent extrusions, (iii) support in the third dimension, and (iv) effects on the extruded sections of the unsteady processing controls. The new design frameworks will be validated against benchmark problems, and experimental testing will be performed to investigate performance. The research has broad societal impacts, as it will enable many applications in diverse fields, including (but not limited to) design of civil structures, aerospace and automotive components, sports and other protective equipment, novel lightweight materials, and biomedical implants. The integrated educational plan includes the creation of STEM-based outreach initiatives for K-12 middle school art class students and teachers. Furthermore, it encompasses courses and research engagement for undergraduate students of engineering and computer science and graduate engineering students.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
