Part 1 of the Computational Engineering Fundamentals delves into a brief historical perspective.


[Editor’s note: Lin Kayser has written a series of stories introducing the new concept of Computational Engineering being developed by his new company, Leap71. This is part one of a six-part series.]

Let’s define what Computational Engineering is and how it differs from the way we currently use computers to design physical parts. If you go back, one hundred, a thousand years, engineering was done with pen and paper. An engineer sat down with all their knowledge about a technical challenge, and then sketched a drawing. Using this sketch, someone was able to build the object that the engineer described.

Over the centuries, the process was refined, the tools became better, and the methodology more and more sophisticated. Up until the 1990s, you could see draftsmen sketching complex machines on their drafting tables. We flew to the moon using slide rules and paper plans. It’s hard not to be impressed by the geniuses who kept the visual aspects of their designs in their heads while they methodically put it on paper.

Obviously, this way of creating designs was very laborious. Iterating was hard because you constantly had to redraw everything from scratch. So it is amazing that some of the most advanced machines, think of an SR-71 Blackbird or a Saturn V rocket, were created using this paradigm.

With the advent of computers, engineers started to digitize this process. Early attempts date back to the 1960s, but momentum really started to build in the 1980s. With the assistance of sophisticated software programs, engineers were able to draw their blueprints more easily, on a computer screen. These were the beginnings of Computer Aided Design, or simply CAD.

But it is important to note what CAD is. It’s a tool that aids you in the visual creation of your design. At first, these tools worked in two dimensions (like the paper they replaced), later, as computers’ capabilities increased, they allowed you to sketch in 3D. But this was also arguably the last fundamental innovation in CAD – allowing you to draw objects in three dimensions, taking out the guesswork of imagining the spatial aspects of your design.

To this day, CAD is what engineers use. All CAD apps are descendants of these early software packages, and all of them share the same visual sketching paradigm — a paradigm that dates back to humanity’s earliest engineers. We use the same process that people used in the Stone Age when they visually described a plan to build something!

CAD applications have come a long way. They give engineers unprecedented flexibility and tools that ease their daily workload. CAD also allows for parametrization of geometries, but anyone who used this feature extensively understands the issues. There are simply limits to the flexibility you can encode into one visual drawing. You might be able to change a few dimensions within reason, but the logic of the sketch, which relies on the dependencies of the drawing process, is very fragile and breaks easily.

CAD was built to aid you in sketching an object. CAD doesn’t “understand” what you are building and cannot fix the drawing for you. This is your job, it’s all in your head. So, even though engineers are using a computer, their work is incredibly manual and repetitive. Some engineers are known to have worked on the same object for years because every iteration essentially required them to start over whenever there was a change request — which takes time, which in turn requires money, which means you avoid it, which translates into “don’t change anything unless you want to go through much pain.” Not a recipe for innovation.

Whenever we see something repetitive, we should immediately think of software algorithms. What engineers do in their heads is essentially algorithmic, using all their expertise to methodically sketch a three-dimensional object. They have years of experience. They know the requirements. They have seen previous objects and weigh their pros and cons. They have an understanding of the manufacturing process and take it into account. While processing this knowledge, they push the buttons and drag their mice and produce a visual part in 3D.

But could this algorithm not also be implemented in software? Instead of engineers executing the process inside their heads and clicking their mice, what if we developed software that could replicate this algorithmic process? By automating the repetitive tasks and leveraging the power of computational technologies, we could revolutionize the field of engineering.

This is where Computational Engineering comes in. By utilizing advanced software algorithms, we can streamline the design process, eliminating the need for manual, repetitive work. Engineers can focus more on innovation and problem-solving, rather than spending their time on tedious tasks. Computational Engineering enables us to explore more possibilities, iterate more quickly, and ultimately push the boundaries of what is possible in engineering.

In the next parts of this series, we will dive deeper into the concept of Computational Engineering and explore the various ways it can transform the field. Stay tuned!

Reinventing Engineering: A Computational Approach

Traditional engineering has long relied on manual processes, with engineers meticulously designing and creating blueprints for construction. But in other fields, like architecture and computer games, algorithms have been used to generate complex structures and landscapes. So why hasn’t engineering embraced this computational approach? It’s time for a change. We need to move away from CAD and towards a future where algorithms take the reins, revolutionizing how we design and build.

The emergence of industrial 3D printing marked a pivotal moment in the push for computerizing the engineering paradigm. Unlike traditional manufacturing methods, which require extensive knowledge of production rules and techniques, 3D printers can fabricate almost anything as long as it meets a few basic constraints. Moreover, these printers allow for intricate detail and the creation of complex lattice structures that were previously challenging to design and produce.

Like many others, I became fascinated with 3D printing during the Makerbot craze. It was during this time that software companies like nTopology paved the way for “Design for Additive Manufacturing” (DfAM) by introducing a new approach to geometry. Instead of relying on blueprints and surface sketches, these packages treated a part as a field of matter, with objects represented as formulas rather than manually placed surface patches. This shift in perspective opened up possibilities for sophisticated infills and intricate structures, sparking my belief that digital manufacturing methods could reshape how we build physical objects.

Motivated by this belief, I decided to leave Adobe, which had acquired my previous company IRIDAS, and delve deeper into this exciting new field. Alongside my co-founder Michael Gallo, we assembled a team and began our exploration of a new engineering paradigm, with a specific focus on 3D printing. After much contemplation, we named our venture Hyperganic, a nod to our mission of going beyond the organic world through computational engineering.

Building Hyperganic meant building from scratch. Existing technologies did not align with our vision, so we knew we had to forge our own path. Our website featured a cheeky teaser trailer, teasing what was to come. We aimed to create a technology stack that supported our disruptive approach, taking into account the needs and requirements of a computational engineering paradigm.

In my next article, I will delve into the technologies we needed to build a computational approach to engineering. I will discuss the choices we made and provide insight into how I perceive the technology stack in this field today. Stay tuned for more on Hyperganic and the future of engineering.

Via Leap71

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