What is Computational Engineering?

Computational Engineering represents a transformative shift in how we design physical objects. Instead of creating a single blueprint through manual CAD modeling, engineers in this paradigm write algorithms that encode the entire design process for a class of objects. The result is not just one part—but a system that can generate many valid designs, all derived from a shared body of engineering logic.

Every object generated through Computational Engineering contributes back to the platform’s codebase, enriching the design knowledge for future iterations. This creates a virtuous cycle where each project increases the capability, flexibility, and sophistication of the system. The more objects you create, the smarter your design platform becomes.

At LEAP 71, we are at the forefront of this new approach. Our work has helped define and advance the field of Computational Engineering, demonstrating that complex hardware—such as rocket engines—can be generated directly from software models that encode physics, manufacturing constraints, and engineering logic. To foster adoption and collaboration, we have released PicoGK, our foundational geometry kernel, as open-source.

A computational engineer begins by breaking down a design into fundamental building blocks, defining how these components interact through clear, logical dependencies. At this stage, the focus is not on aesthetics, but on capturing the essential rules: functional requirements, physical constraints, manufacturability, and performance criteria.

The next step is to encode the construction logic—answering the question: Given these constraints and inputs, how would a domain expert approach the design? This initial implementation may produce simple placeholder geometry, but it establishes the structure on which more sophisticated algorithms can be built.

Through iteration, the computational model is refined, gradually introducing higher levels of design intelligence. Engineers validate the outputs across a wide parameter space, using visual inspection, physical testing, and increasingly, automated numerical simulation.

The result is a living computational model: software code that accepts parameters and production constraints as input and outputs manufacturable designs as directly printable or machinable files.

This model can be deployed at scale, reused, extended, and improved by other engineers. It becomes not just a design—but a scalable, evolving platform and a new form of intellectual property: a dynamic, codified knowledge base for the creation of physical products.

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