Deadline:
As soon as possible
Location(s)
Italy
Levico Terme, Trento
Overview
Details
The objective of the internship is to investigate numerical methods of analysis and simulation to study the capacitive coupling between a laser cutting machine sensor and the tube, depending on the distance and shape of the tube.
The candidate will have to build a numerical simulation model to estimate the capacitive coupling between a nozzle of known shape and a work-in-process tube of arbitrary shape. To do so, the candidate will need to study the state of the art of known techniques, including FEM, BEM and reduced bases. Having identified the most promising model, the candidate will have to implement it in software suitable for “offline” operation and possibly also in “online” software running realtime on the laser cutting machine. Thus, simulation/processing time is one of the most stringent targets of the model under study.
Activities and topics covered:
- State-of-the-art study and choice of simulation techniques appropriate to the target;
- “Offline” implementation and experimental validation of capacitive coupling between head and material at different distances and for different shapes;
- “Realtime” implementation of the algorithm for generating optimized trajectories;
- Experimental validation on BLM GROUP's numerically controlled machine.
Note: The trainee will be expected to work within the workplace with the utmost respect for the rules established to ensure Safety and Health, their own and others', and to ensure optimal functioning of the work environment.
Opportunity is About
Eligibility
Candidates should be from:
Description of Ideal Candidate
Prerequisites:
- Bachelor's or Master's degree (Mechatronics Engineering, Industrial Engineering, Physics, Mathematics), pending;
- Methodological knowledge of FEM (finite element) and/or BEM (boundary element) analysis;
- Knowledge of the English language (level B2).
Preferred requirements:
- Knowledge of “reduced basis” method for efficient simulation of complex models.
Dates
Deadline: As soon as possible
Cost/funding for participants
Un-save Opportunity
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