Rethinking Infrastructure Deconstruction Through Reality Data Capture and Interactive Simulations

Abstract

The demand for careful infrastructure deconstruction and disassembly increases every day, as the market for building material reuse grows, and the reality of construction landfill waste weighs on the environment. Mid-century nuclear power plants are one example of infrastructure that are reaching life expectancies and require massive deconstruction initiatives. These projects span multiple decades and bear massive costs, making effective planning a requirement. However, despite active research efforts in infrastructure lifecycle stages such as design, construction, inspection, and maintenance, deconstruction remains relatively unexplored. Meanwhile, applicable technologies like autonomous robotics, virtual reality headsets, and 3D simulation software are more capable and cost-effective than ever. In this research, the use of reality data capture and virtual reality simulations as tools for planning deconstruction projects is studied. Novel planning workflows using these technologies are designed, implemented, and tested for validation. The completion of this research yields the contribution of three novel planning methodologies. They are 1) a methodology for cutting and packing planning, 2) a methodology for building material reuse planning, and 3) methodology for automated critical path schedule generation. Several scientific problems are addressed in support of developing and validating the proposed methodologies. While the methodologies each address a different workflow within deconstruction planning, they build upon each other in terms of the scientific problems that are addressed, with the final methodology bearing the most significant and novel contributions. In the methodology for cutting and packing, the topics of creating immersive virtual reality simulations from reality data as well as conducting human-computer collaborative cutting and packing planning based on reality data are addressed. An optimal reality data processing approach for deconstruction planning simulations is detailed based on a quantitative comparison of reality data capture methods as well as qualitative observations. A simulation environment with rich feedback based on the processed reality data is designed to enable human-computer collaborative cutting and packing planning. These developments build upon prior work with similar capabilities, but that do not incorporate reality data. In the methodology for building material reuse planning, the problem of simultaneously optimizing deconstruction planning and reuse-based architectural design is studied. A gamified virtual reality simulation is developed and presented to address the underconstrained nature of this problem, which enables users to create a high level initial solution. A workshop with human participants is held and quantitative metrics from questionnaires as well as qualitative feedback on the simulation is collected. The feedback is analyzed in order to support future work in refining the methodology. In the methodology for automated critical path schedule generation, the most significant contributions of the thesis are presented, where the problem of efficiently and automatically generating accurate critical path schedules based on a virtual reality simulation run is addressed. In the methodology presented, a series of novel algorithms are designed to deduce the requisite information to produce a critical path schedule that reflects a user’s actions in a virtual reality environment. The algorithms support 1) detecting the occurrence of construction-centric actions within the virtual reality environment, 2) estimating the corresponding real-world durations of detected actions, and 3) deducing the precedence relationships of detection actions. Using this information, an automated approach for assembling a critical path schedule that is enhanced with rich metadata about the planning process and that is not resource constrained is presented.