One technology that is often referred to in the context of additive manufacturing and 3D printing is engineering simulation. In contrast to additive manufacturing – which can directly create physical products from virtual designs – engineering simulation allows engineering professionals to virtually investigate the behavior of products and assemblies.
By Milad Mafi, SimScale GmbH
Various physical phenomena such as flow, structural mechanics, acoustics, and thermodynamics can be considered and evaluated. For instance, automotive manufacturers have been working on crash simulations for more than 20 years, which enable the safety of their vehicles to be optimized during the ongoing development process long before manufacturing any physical prototype.
Both technologies show a striking overlap in their historical development and commercialization. Thus, in both cases, it is a scientific utopia that was realized for the first time at the end of the last century. For a long time, engineering simulation was reserved for only a few investment-intensive industries such as aerospace and automotive engineering.
In the last ten years, recent innovations helped to massively decrease the cost of running these technologies, which made them more and more available to a larger audience of engineers, scientists, and hobbyists.
However, engineering simulation, which is also known as computer aided-engineering (CAE), can help to boost the development of devices for additive manufacturing. In this article, we will introduce you to the concept of engineering simulation and highlight how it can be leveraged to optimize different components of an open source 3D Printer.
Fundamentals of Engineering Simulation
Simulations are based on known laws and fundamentals of physics, which are essentially based on mass, pulse, and energy conservation. These equations have already been formulated and described for the first time in the 18th and 19th centuries.
It was not until 100 years later, however, that this milestone of science could be applied to engineering problems. The reason is to be found in the mathematical properties of these equations, which can not be solved analytically, but numerically, for real world phenomena.
Numerical in this context means that the equations are discretized in time and space. The desired sizes such as, for example, the temperature distribution in an extruder, is only calculated for discrete points and time steps determined by the user. For this purpose, the geometry to be examined is decomposed into elements of geometric basic bodies, such as hexahedra and tetrahedra.
Only with the rise of computer technology in the second half of the 20th century, it became possible to solve this very large system of linear equations and therefore simulate the motion of fluid substances or the stress distribution inside a solid material. At the time, as nowadays, simulation was a trade-off between accuracy and time: even today’s most powerful supercomputer would need years to predict the flow field around a small object without major simplifications like the usage of turbulence models and time-related averaging.
Optimization of a RepRap 3D Printer
However, simulation is more than a virtual experiment: While in a physical test, only the quantities recorded during the test are available for evaluation, CAE provides a complete picture of the physics. This enables engineers not only to understand what but also why it is happening.
In the following, the application possibilities of CAE will be shown using the example of the RepRap Mendel. This is an open source 3D printer, which has been widely distributed due to its low costs. Technically, this is based on the FDM process, in which a thermoplastic filament is extruded through a nozzle.
The temperature distribution in the extruder has a very great influence on the quality of the parts produced. Having a non-disturbed temperature at the print bed is a key ingredient in obtaining a good result. With simulation tools, we can now precisely investigate the thermal behaviors of the hot-ends. We can simulate air flow over print beds to determine if temperature stays at desired levels. And we can even investigate the influence of the printer’s elements on the thermal balance of the system: do the motors overheat? Do they affect the mounting points and can cause them to bend?
Another promising application of simulation is to check if the designed plastic elements of the printers would hold the loads and withstand the stresses imposed on them. A vibration analysis allowed to determine areas undergoing periodic loads which could result in, for example, screws getting loose, or worse — the 3D prints getting distorted.
Shifting to the Cloud
Comparatively, the high computational effort is still one of the cost drivers of simulation. This is particularly challenging for small engineering firms and companies, combined with the required flexibility. The availability of cloud computing and related products such as software as a service (SaaS) will significantly reduce barriers and provide access to simulation on demand.
An example is SimScale, which is the world’s first 100% cloud-based simulation platform, allowing engineers to perform powerful CFD or FEA simulations by using any laptop, PC or tablet, at a fraction of the price of traditional on-premises software. With a clear mission of making simulation accessible to every engineer in the world, SimScale provides a free Community plan and a 14-day free trial for the Professional account.
Want to give it a try? Create a free Community account at www.simscale.com.
If you’re interested in how you can use simulations for optimizing 3D printers, the DIY 3D Printer Workshop is a great place to start.