Key Skills

Job Description

Job Description Thermoplastic composites are widely regarded as promising materials for the next generation of commercial aircraft, combining excellent mechanical performance with low weight. In addition, their melt-processable matrix enables automated, high-rate manufacturing of components that can subsequently be assembled into complex aerostructures using welding. This provides significant opportunities for more efficient and cost-effective aircraft manufacturing. However, welded composite assemblies are challenging to inspect using conventional non-destructive inspection techniques. As a result, larger safety margins are often required in structural design, leading to heavier structures, while maintenance intervals may be more conservative than necessary. Developing reliable methods to continuously assess the structural condition therefore enable both lighter designs and more efficient maintenance strategies. To address this challenge, the project aims to develop structural health monitoring technologies based on a digital twin. The digital twin will combine information from the physical structure with models and monitoring data to assess its current structural state and predict its remaining lifetime. This will enable the condition of welded structures to be monitored throughout their service life, allowing maintenance to be planned when it is actually needed rather than according to predetermined intervals. Ultimately, this approach aims to contribute to lighter, safer, and more sustainable aircraft structures. The PhD positions Experimental characterization and digital twin development A key challenge in developing a reliable digital twin is accurately characterizing the static and fatigue behaviour of welded thermoplastic composite joints. Since there are currently no well-established standards for fatigue testing of these joints, the project will involve developing experimental methods to reliably characterize their mechanical performance and damage evolution. The experimental results will be used to develop constitutive models for the welded interface. In particular, these models should describe progressive interfacial damage development as a function of fatigue loading. The models will be implemented and validated in commercial finite element (FE) software. The resulting FE model will define the digital twin of the welded structure and provide the basis for the second PhD project, which will use the digital twin together with monitoring data to develop prognostic structural health monitoring strategies. In this project you will: Perform experimental characterization of the static and fatigue performance of welded thermoplastic composite structures. Develop constitutive models that accurately describe the performance of the welded interface. Implement the developed models in commercial FE simulation software for the development of a digital twin and validate their accuracy against experiments. We are looking for a colleague who has experience in mechanical experimentation of the fatigue behavior of composite materials and/or polymers, and is able to develop and implement constitutive models in FE software. Development of a Structural Health Monitoring system The ability to estimate the current state of the welded thermoplastic composite joint and the development of this state over time, is of decisive importance for lifetime performance modelling. The key challenges are the robust integration of a sensor system in the structure and the analysis of measured signals, which are typically strongly affected by environmental and operational conditions. This project aims to tackle these challenges by using piezo-electric and/or optical fiber based sensor system, combined with physics informed data analysis method, exploiting the digital twin model developed by the first PhD project. In this project you will: Implement an effective sensor integration method for welded thermoplastic composite structures, using piezo-electric sensors, fiber optical sensor, or a combination of both. Perform dynamic experiments of pristine and (gradually) damaged structures to collect data for the state estimation methods. Develop signal processing methods to estimate, enriched by physics-based information, the current state of the welded structure and its development under fatigue loading. We are looking for a colleague who has experience in sensor integration and dynamic experimentation, knowledge of piezo-electric or optical fiber based measurements, and proficiency in signal processing methods enriched with physics-based information. Your profile You are a highly motivated researcher who is driven by curiosity and has: A Master’s degree in Mechanical Engineering, Aerospace Engineering or equivalent. Good team-working abilities and a positive can-do mentality. Strong reporting and communication skills Proficiency in English, both spoken and written (we require a TOEFL > 90 or IELTS > 6.5 score). Further, the position on fatigue characterization and mechanical modelling requires: Experimental skills in the mechanical characterization of fiber reinforced composites or polymers; experience with fatigue testing is desired. Theoretical knowledge and skills in the modelling of (failure) of fiber reinforced composites. Experience with the finite element method and programming experience in scripting languages like Python or Matlab. The position on structural health monitoring requires: Experimental and theoretical skills in dynamics and experiences with piezo-electric and/or fiber optic sensors. Experience with signal processing methods of data, enriched with physics-based information. Our offer We offer a full-time 4-year Ph.D. position with a qualifier in the first year; excellent mentorship in a stimulating research environment with excellent facilities; and a personal development program within the Twente Graduate School. It also includes: You will receive a gross monthly salary ranging from € 3204 (first year) to € 4051 (fourth year). Excellent benefits including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, a solid pension scheme, and 29 vacation days in case of full-time employment. A training program, where you and your supervisors will settle a plan for education and supervision. Excellent laboratory and support facilities, as well as a diverse team of enthusiastic colleagues and supervisors. A green campus with free access to sports facilities and an international scientific community. A family-friendly institution that offers parental leave (both paid and unpaid). Information and application Please submit your application before October 15th using the “Apply now” button, and include: A Curriculum Vitae, including contact information for at least two academic references. An original cover letter of at most one page. In this cover letter you will indicate your preferred PhD position (only one) and explain why you believe you are the best candidate, while referring to your background knowledge and past experience. A three-minute video where you introduce yourself and explain why you applied for the position. Transcripts from your Bachelor and/or Master degrees. Interviews are planned in the last week of October. A knowledge security screening is part of the application procedure. Additional information about this position can be acquired from dr.ir. Wouter Grouve ([email protected]). About The Organisation At the Faculty of Engineering Technology (ET), we work on engineering for impact: developing smart, sustainable, human-centred and technological solutions for societal challenges. We connect fundamental education, research and practice across five core domains: Asset & Maintenance engineering, Intelligent Manufacturing Systems, Personalised Health Technology, Resilience Engineering, and Sustainable Production, Energy and Resources. We work on education and research in mechanical engineering, civil engineering and industrial design engineering. Together, we learn by making, creating, and innovating, addressing challenges in a solution-oriented way. Quality, connection and inclusivity are the foundation of our culture. In our open community, students, researchers and staff collaborate with industrial and societal partners. This enables us to develop insights, applications and solutions that add value to society.

Core Responsibilities

Develop structural health monitoring technologies and digital twins for welded thermoplastic composite assemblies. Responsibilities include performing experimental characterization of fatigue behavior, developing constitutive models, and implementing sensor systems for state estimation.

Requirements

Candidates must hold a Master's degree in Mechanical or Aerospace Engineering with proficiency in English. Specific requirements vary by project, focusing on either mechanical modeling and FE software or sensor integration and signal processing.

Benefits

• Holiday allowance of 8%
• End-of-year bonus of 8.3%
• Pension scheme
• 29 vacation days
• Training program
• Laboratory and support facilities
• Free access to sports facilities
• Parental leave