Date of Award

Fall 12-2017

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computing

School

Computing Sciences and Computer Engineering

Committee Chair

Dia L. Ali

Committee Chair Department

Computing

Committee Member 2

Chaoyang Zhang

Committee Member 2 Department

Computing

Committee Member 3

Beddhu Murali

Committee Member 3 Department

Computing

Committee Member 4

Ras B. Pandey

Committee Member 4 Department

Physics and Astronomy

Committee Member 5

Bikramjit Banerjee

Committee Member 5 Department

Computing

Abstract

Thanks to advances in Additive Manufacturing (AM) technology and continued research by academics and entrepreneurs alike, the ability to “3d print” permanent concrete structures such as homes or offices is now a reality. Generally, AM is the process that allows for a 3d model of an object to be converted into hardware instructions to generate that object layer by layer using a malleable medium such as a plastic. Specifically, large scale concrete AM can now generate a structure, such as a building, layer by layer more quickly and efficiently than traditional construction methods [6, 39]. This innovative, semi-autonomous process promises many improvements over traditional construction methods, but it also introduces new challenges to be overcome. The increased level of automation, the accelerated construction speed, and costly nature of defects are all important factors that emphasize the need for a thorough review of the final hardware instruction sets before production of the project ever begins.

In this research, we propose and explore five methods to help verify model integrity of the print instructions: visual inspection of the design elements, using Fuzzy Logic to predict thermal stress, extrusion end point evaluation, pathing collision checks, and ray tracing for identification and analysis of overhangs. While these methods are not all inclusive, they will help to identify potential defects and high risk design elements in the pre-production phases of a project.

Collectively these five verification methods proposed serve as a starting point for verifying model integrity. These verification methods derive detailed information from the instruction sets, execute various simulations and data analysis, and provide feedback to improve the overall model design and print process. Additionally the simulation process described herein can be built upon to produce other methods of verification. Earthquake or wind resistance tolerances could potentially be verified using existing model data and material data.

Lastly these verification methods will be actively applied across a case study for a proposed wall along the southern border of the United States. This applications was selected specifically because Additive Manufacturing should clearly have substantial benefits over traditional hands on construction methods for this project. A concrete wall without any of the intrinsic complications of lived in buildings, may prove to be an outstanding killer application of 3d printing technology. Not only is the border wall used as a test case for the verification methods, but it also serves as a cost analysis to predict the cost benefits of 3d printing simple mostly automated projects. The author does not endorse any political stance by proposing this case study. The case study is purely a scientific endeavor to explore the feasibility of concrete structures outside the scope of traditional buildings. Additional applications of the research could include water levees, dams, and perhaps even bridges. The construction of large scale concrete infrastructure may prove to be an ideal problem domain for Additive Manufacturing.

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