Construction-Scale Concrete Additive Manufacturing and its Application in Infrastructure Energy Storage
Conventional construction is a labor intensive, hazardous, expensive, inefficient, and wasteful process. According to the EPA, 534 million tons of construction debris were generated in the United States in 2014, which is more than twice the amount of generated municipal solid waste. In addition, conventional construction materials are often used inefficiently and with poor quality control, resulting in buildings with poor thermal performance. Infrastructure-scale additive manufacturing (AM) that is both scalable and portable has the potential to revolutionize the construction industry by enabling automation and expanding the design space for new installations.
The emergence of large-scale AM systems was partially enabled by commodity-grade feedstocks, such as polymer pellets or metal wire. However, infrastructure-scale AM components will weigh hundreds of thousands of pounds, making these materials are far too costly to be considered in infrastructure applications. However, concrete is the most cost-effective feedstock; it only costs pennies per pound.
While many concrete additive systems have been developed, they are typically gantry- or robotic-arm-based. This poses challenges for on-site, large-scale manufacturing. For the majority of the systems presented to date, significant site preparation would be required. Furthermore, to achieve the required build envelopes, the system must be larger than the structure being fabricated. This necessarily leads to gantry systems or robotic platforms that are prohibitively large, expensive to transport, set up, and operate, and difficult to position with the precision necessary.
In this paper, a portable and easily deployable cable-driven large-scale concrete AM system is presented. The system utilizes four base stations, which are deployed independently and connected to the deposition head with a series of cables. By precisely controlling the cable lengths, the deposition head can be repeatably positioned to within 0.3 cm over a large workspace. An integrated laser measurement system is used to track the deposition head. The laser measurements are used by a feedback control system to enable precise positioning.
To demonstrate this system, a wall has been developed to be printed at the Federal Energy Management Program (FEMP) conference in August 2020. The exterior of the wall, shaped to maximize heat transfer, is printed to act as form work and serve as a mounting surface for an energy-storage system. Two-inch-thick iso-foam is used to insulate the internal concrete from the exterior, providing a large internal mass for energy storage. Embedded water lines serve to cool the internal concrete, storing energy during off-peak periods. A hydronic system is used to, in effect, ‘turn off’ the insulation, allowing energy to be transferred from the interior to the exterior surface, reducing the peak demand on a building’s HVAC system. Three of the proposed walls will be installed in commercial buildings for field validation.
Construction-Scale Concrete Additive Manufacturing and its Application in Infrastructure Energy Storage
Category
Technical Paper Publication
Description
Session: 02-02-02 Conference-Wide Symposium on Additive Manufacturing II
ASME Paper Number: IMECE2020-24012
Session Start Time: November 17, 2020, 03:40 PM
Presenting Author: Joshua Vaughan
Presenting Author Bio: Joshua Vaughan is currently an Associate Professor in Department of Mechanical Engineering at the University of Louisiana at Lafayette. While on a leave-of-absence from that appointment, he is working as an R&D Staff Member within the Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory (ORNL). Dr. Vaughan received his Ph.D. from the Georgia Institute of Technology in 2008. Upon graduation, he completed postdoctoral appointments at Tokyo Institute of Technology and Georgia Tech, then joined the faculty at the University of Louisiana at Lafayette (UL Lafayette) in August of 2012. Dr. Vaughan's current research interests include the integration of conventional control methods and machine-learning-based controllers, multi-agent additive manufacturing, mobile robotics for inspection and search-and-rescue operations, and autonomous maritime systems.
Authors: Joshua Vaughan University of Louisiana at Lafayette
Celeste Atkins Oak Ridge National Laboratory
Alex Boulger Oak Ridge National Laboratory
Phillip Chesser Oak Ridge National Laboratory
Jessie HeinemanOak Ridge National Laboratory
Diana Hun Oak Ridge National Laboratory
Melissa Lapsa Oak Ridge National Laboratory
Amy Loy Oak Ridge National Laboratory
Alex Roschli Oak Ridge National Laboratory
Peter Wang Oak Ridge National Laboratory
Brian Post Oak Ridge National Laboratory