Embark on a pioneering master thesis journey with Combitech Trollhättan, where you will be at the forefront of optimizing additive manufacturing processes within the Aerospace sector. As the defense industry continues to grow, Combitech is expanding its capabilities to support this growth. This 30 hp project involves leveraging your academic insights into Applied Mechanics and Python coding skills to devise a novel algorithm that enhances DED AM simulations. Your work will enable rapid production of intricate components while reducing heat-induced distortions and stresses, aligning with Combitech’s mission to drive innovation in defense technology.
Background
The Aerospace industry dreams of leveraging additive manufacturing technology for rapid design and producing complicated massive flight ready components without the need of complex tooling. For this reason, direct energy deposition, where a structure is created though continuous welding seems suitable, however; the immense heat used poses an obstacle as it tends to heavily distort and build in high residual stresses in the components. It also slows down the production speed one often needs to stop the building of the massive components to let the heat dissipate, mitigating distortion problem and failed prints. Researchers have proven it is possible to use Finite Element Analysis to predict distortion – even though slow – thermally induced stresses and now we aim to use it to overcome the heat obstacles for the flight ready printed components and systems. Join us in the pursuit to overcome this heat barrier preventing rapid DED manufacturing simulations using FEA to produce insightful design support for real flight ready structures.
Objective
You will leverage your knowledge obtained from your studies to implement an algorithm (using Python) that allows course mesh representing multiple AM deposition layers to be used for DED AM simulation. You will then use this algorithm on a validation model where an aircraft skin and frame are integrated together. Further as the weld robot weld in stages and in multiple direction the FE setup you setup should also consider simulation of material deposition in multiple directions (height and radial directions) mimicking the real manufacturing print. You will use commercial CAE tools (Marc and Simufact AM by Hexagon) to model and analyse the DED AM manufacturing process with the aim to simulate the complete DED AM printing sequence of massive structures within hours rather than days or weeks, enabling Saab to use it to print ever larger and more complex AM structures.
In short:
- Literature study and fact gathering
- Development of course FE models of a printed geometry and compare distortions to measurement
- Develop a property scaling algorithm that scale element properties due to geometrical filling of printed geometry
- Create shape compensated geometry that mitigates distortion and thermal stresses
- Recommendations, report writing and presentation.
Who are you?
We are looking for two Master program students, Mechanical engineering with specialization in Applied Mechanics or equivalent, studies in Additive Manufacturing simulation and programming using Python are beneficial. The work will be carried out at Combitech office in Trollhättan in close collaboration with Saab Aeronautics in Linköping.
As the position involves work that is covered by confidentiality, it is required that you complete and pass a security assessment.
Selection is ongoing. We look forward to your application!
Make a difference
We at Combitech are accelerating the development of a smarter, more sustainable and more resilient society. By combining our solid experience within defence- and industry sectors, we contribute to society by enabling the industry, total defence and communities to withstand the challenges and leverage the opportunities of tomorrow.
As a Nordic tech solution and consulting partner with 2200 passionate, highly skilled experts at our core, we partner with our customers to push the boundaries of technology and make a difference.
CONTACT
Tobias Persson +46 73 4186478