Background Segmental construction is an effective method of developing large-scale projects, like bridges, over or around natural obstacles. Highly mechanized methodologies are used to build precast concrete sections or segments that can be joined and stressed together, drastically accelerating bridge construction. Precast segments, incremental launching and the balanced cantilever method all offer a fast, efficient, and versatile alternatives to traditional construction techniques. Despite their widespread use, these methods are disadvantaged in their available margin of error – tolerance during segmental construction is typically less than millimeters, requiring extreme precision to eliminate any misalignment errors. In addition, segmental construction is currently reliant on falsework or forms to develop segments, increasing overall project cost for both components and necessary labor. Thus, there is a need for a cost-effective, efficiently paced, precise, and versatile alternative to mold-based segmental construction. Technology Description Researchers at the University of New Mexico have utilized a concrete additive manufacturing (AM) methodology to eliminate the need for formwork in segmental structure construction. The transition from mold-based techniques (falseworks, forms, or molds) to AM allows precast incremental segments of a superstructure to be 3D printed, assembled, post-tensioned, and efficiently grouted; thus, reducing the construction time, labor, and cost typically compiled via traditional formwork. Various polymer concrete filaments can be utilized to attain unique geometries, while still maintaining high durability. The use of 3D printing and digitalization benefits the completed segment, by enhancing construction management, reducing errors, and narrowing the existing gap between structural engineering and design. Though primarily directed toward bridge construction, this invention can also be utilized to create concrete slabs, walls, columns or other elements subject to segmental construction. Andrew Roerick aroerick@innovations.unm.edu 505-277-0608
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