In May 2022, Hyperganic built the world's largest 3D-printed Aerospike rocket engine. It's also the most complex 3D-printed object to date. Standing at 80 cm tall and printed from copper on an AMCM machine, it's the first algorithmically engineered rocket engine, designed entirely using the Hyperganic Core software platform.
The Aerospike rocket engine concept is not new by any means and has been around since the 1960s and 1970s. From a theoretical perspective, the engine is renowned for its altitude-compensating concept, which promises a performance advantage of up to 20 percent over traditional bell nozzles during atmospheric ascent.
With that goal in mind, prototypes were built by Rocketdyne and NASA, but never left the test stands. The Space Shuttle was originally meant to have an Aerospike to unlock Single-Stage-To-Orbit (SSTO) capabilities. But that never happened as the engineers could not overcome the inherent challenges of the Aerospike concept, given traditional design and manufacturing methods. For example, the central spike that facilitates the supersonic exhaust gas expansion is prone to overheating and melt-down if not cooled sufficiently. While the Aerospike's compact design makes it ideal for small, orbital launchers, it also increases the heat load significantly.
Advanced 3D-printing methods have made it possible to incorporate regenerative cooling channels directly into the manufactured part. Some New Space startups, like Pangea Aerospace, are already metal 3D printing and testing prototypes. However, the full potential of additive manufacturing (AM) and its design freedom has not been unlocked, and Hyperganic intends to change that with its Algorithmic Engineering paradigm.
Algorithmic Engineering uses computer code to create physical objects algorithmically and automatically. One can think of the algorithms as step-by-step instructions for a computer to mimic what an engineer would do. The difference is that computers are scalable with computational power and can work tirelessly to resolve a problem to a level of detail that a human engineer could not achieve. The goal is to accelerate innovation in physical products in the same way that Moore's Law of exponential growth fuelled innovation in the computer industry.
As the algorithmically engineered objects can evolve to highly complex designs, the technology works hand-in-hand with AM methods. Ideally, the algorithms are informed by the 3D printer's constraints, and can never generate a part that is not manufacturable on that machine.
Algorithmic Engineering speeds up the iteration cycles to seconds or minutes, rather than the weeks or months that engineers typically experience. That advantage allows engineers to free up the time spent on manual, laborious CAD drawings to explore a much larger solution space and focus on system level optimizations. The fast iteration cycles also spark technical innovations since it gives them more room to explore different configurations and learn quickly from mistakes.
Unlike traditional CAD applications, an engineer using Hyperganic Core encodes his or her knowledge of the design process into computer algorithms. The Aerospike engines were generated through the same algorithm but with different input parameters in order to conform to different specifications. Each physical component within the engine is represented by a code module. The software and physical architecture are similar. These components exchange information such that a change in one component automatically propagates through the entire assembly to always result in a valid design.
The entire process took only minutes to run and completely reengineered the Aerospike design from scratch to conform to the new specifications. The engine was printed on the EOS M 400-4 industrial 3D printer with zero support using the EOS NickelAlloy IN718 process. A larger 80-cm version of the aerospike was automatically reengineered for production on the AMCM M 4K 3D printer in EOS CopperAlloy CuCrZr.
Both engines feature many interesting design aspects. Multiple combustion chambers enable thrust-vectoring. The chambers’ cross-sectional areas are driven by a desired Mach number distribution and calculated through the isentropic flow conditions.
Algorithmic Engineering enabled regenerative, dual-propellant cooling circuits to be automatically routed across the walls of the individual combustion chambers. The injector head consists of mass-customized co-axial swirl injectors. Each injector element is optimized based on its distance to the wall for a given combustion temperature distribution. All manifolds and internal routings adapt their local overhang angles to ensure printability, by dynamically changing their cross section between round (vertical print orientation) and rhombic (horizontal print orientation).
“This Algorithmic Engineering approach is a game changer for innovation in physical objects because of its ability to generate fast engineering cycles,” said Josefine Lissner, Strategic Engineering Lead at Hyperganic. “I expect it to be the next disruption in the space industry, where progress is hampered by the prohibitively high cost of design iterations. Once a company establishes this new process successfully, it will be impossible for competitors to keep up using a manual CAD approach.”
Rocket engines are by far the most expensive part of an entire launcher, as the development process requires a lot of time, money, and human labor. Hyperganic's platform enables engineers to accelerate the design process by using existing software modules without any manual involvement, thus dramatically decreasing the cost of space travel. Through Algorithmic Engineering, the space sector can now build novel propulsion systems like the Aerospike concept in less time with less money.
This new engineering paradigm is not limited to space propulsion but also relevant to all other engineering domains, including industrial and automotive applications, heating and cooling, bio-printing, and next-generation consumer products.
This article was contributed by Hyperganic (Munich, Germany). For more information visit here .