The carstensen group is an interdisciplinary engineering lab at MIT focusing on developing new rigorous methods and algorithms that can improve structural design.
The digitalization of manufacturing is radically changing how we fabricate and construct structures. Today we can make things that were too complex for manufacture just a few years ago. To fully leverage the new manufacturing possibilities and make our structures lighter, faster, safer or any other objective we seek, we need to re-think our approach to structural design. In the carstensen group we work with developing structural- and topology optimization frameworks that improves design. We work with design at the conceptual stage, develop algorithmic details for implementation of new manufacturing considerations and take optimized designs out of the computational space to experimentally investigate their behavior. We are based at MIT in the Department of Civil and Environmental Engineering. The structures we are interested in can have any size; it can be a high-rise building, a part or component of a larger structure or the architecture of a porous material.
This work presents an experimental investigation of the effect of ribbing patterns overlayed on waterjet cut steel plates when using them as reinforcement for concrete. A key takeaway is that we can get within 90% of the pull out force of regular rebar just by varying the ribbing pattern. This opens up opportunities for prototype and scale testing of new civil structural designs.
Timber-Steel Trusses with Minimized Embodied Carbon
There is an increasing need for automated design processes that can help guide structural design towards lower embodied carbon solutions. This research presents a two-material truss topology optimization algorithm that aims at reducing the Global Warming Potential (GWP) of the designed structure. The framework is demonstrated on truss designs with a mix of glue-laminated timber (GLT) and steel elements for both 2D and 3D design examples.
Cellular Materials with Maximized Energy Absorption
Topology optimization is increasingly being used to design the architecture of porous cellular materials with extreme elastic properties. This project seeks to extend the design problem to the nonlinear regime and aim to maximize the energy absorption. Designs are obtained, fabricated and tested with bulk metallic glass as the base solid.
Topology Optimization of Rigid Interlocking Assemblies
Traditionally, interlocking assemblies are used in carpentry and associated with a set of quintessential shapes that are governed by the traditional cutting tools for wood. With today’s manufacturing, both ease of fabrication and design options are dramatically changed to give this type of connection renewed relevance and development potential as it can lock components in place without using of adhesives or fasteners such as mortar, glue, bolts, nails or screws.
Topology optimized design is tailored to fabrication by material extrusion processes by incorporating a discrete nozzle size constraint. Material extrusion processes are used in a range of 3D printing technologies; from bio printing for tissue engineering, over Fused Filament Fabrication to Big Area Manufacturing and Concrete 3D printing.
Topology Optimization with Nozzle Size Restrictions for 3D Printing
Two Phase Minimum and Maximum Feature Size Control in Topology Optimization
Reinforced Concrete (RC) beams are designed using an existing hybrid bi-linear topology optimization algorithm for design of Strut-and-Tie models. The reinforcement layouts are water jet cut from steel plates and placed into the concrete during casting. The beams are experimentally tested to investigate the performance of the designs. Behavioral improvements are found even at low levels of complexity.
Topology-Optimized Reinforced Concrete Beams
Concrete beams are designed using existing topology optimization algorithms and cast into falsework that is fabricated with digital tools. The beams are experimentally tested to investigate the performance of the design algorithms outside the computational domain.