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on the fabrication of functional materials with enhanced properties for industrial applications using the laser powder-bed fusion (LPBF) process. Particular attention will be paid to alloy design, parameter
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modeling and computational tools, the project will establish process-structure-property relation- ships that connect LPBF parameters with microstructural evolution and mechanical performance. These insights
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model, which maps online observable process parameters (e.g. spinneret voltage, flow rate etc.) to nanofiber product quality (e.g. morphology, diameter variance, all of which are only observable offline
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-based control of multilayer electrospinning. The task of the PhD student is constructing a scalable, multiparameter model, which maps online observable process parameters (e.g. spinneret voltage, flow
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real-time application from MATLAB/SIMULINK for the target machine Set up and tune signal parameters from within MATLAB/SIMULINK during real-time execution Practical tests on the test bench • The test
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physical and chemical parameters of wastewater and assess the biodegradability of various bioplastics. The research group has developed several edu- cational materials on LCA and sustainability topics in
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per- formed against previous reactor technologies with which UKNNL has experience. Sensitivity and uncertainty analyses will examine the effects of varying key parameters such as waste volumes
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partners. Applicants should fulfil the following requirements: A master’s degree in engineering or science, with a focus on computer/data systems, energy technology, software/hardware, information technology
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of the computer languages Knowledge of IoT Working on board ships The candidate is expected to submit a research plan to show their knowledge of ship speed-power performance. The plan should include a