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PhD Position: Improved Temper Roll-Force Prediction Through Microstructural Modelling
University of Twente

PhD Position: Improved Temper Roll-Force Prediction Through Microstructural Modelling

2025-06-15 (Europe/Amsterdam)
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Job description

Steel is extensively used in sheet form across a wide range of applications. Two critical processes that significantly influence the usability of steel sheets are annealing and temper rolling. Annealing resets the material's microstructure, enhancing strength and formability, but it can also lead to the undesirable yield point phenomenon. This phenomenon causes localized deformation known as Lüders bands, which adversely affect the material's mechanical properties and surface quality.

Temper rolling is employed to eliminate the yield point phenomenon, but accurate prediction of the roll force during this process is challenging due to a lack of understanding of the underlying microstructural mechanisms. If the roll force is not precisely controlled, it can negatively impact the final properties of the steel sheet, undermining previous optimization efforts and increasing scrap rates.

This project aims to develop a new material model based on an improved understanding of the yield point phenomenon through innovative testing and microstructural modelling. By focusing on the mobility and density of dislocations that contribute to plastic deformation, this physics-based approach will enhance predictive capabilities. The model will be integrated into temper rolling simulations to accurately predict roll force, surface properties, and microstructural outcomes. Additionally, it will facilitate fast, online prediction of roll force, directly impacting scrap reduction and process efficiency.

Your Role

  • Participate in cutting-edge research under the guidance of leading experts in the field.
  • Develop a novel constitutive material model that incorporates the yield point phenomenon at the macroscale.
  • Design and conduct mechanical characterization experiments (e.g., uniaxial tensile tests, shear tests) using advanced techniques like Digital Image Correlation (DIC).
  • Implement the material model in finite element simulations (e.g., using Abaqus) to simulate the temper rolling process.
  • Enhance existing analytical tools for fast and accurate roll-force prediction.
  • Collaborate with an interdisciplinary team, including members from the University of Twente and industrial partner Tata Steel Europe.
  • Report your research findings in bi-weekly meetings and at international conferences.
  • Prepare and publish your research in high-impact academic journals.
  • Complete a doctoral thesis within the project duration.

Your profile

  • A master’s degree in Mechanical Engineering, Materials Science, Applied Physics, or a closely related field, with excellent academic records.
  • Strong background in solid mechanics, material modelling, and finite element analysis.
  • Proficiency in programming and numerical methods; experience with Abaqus and user subroutines (UMAT/VUMAT) is advantageous.
  • Experience with experimental mechanics and material characterization techniques.
  • Excellent analytical and problem-solving skills.
  • Independent, responsible, and highly motivated with strong analytical skills.
  • Excellent communication skills in English, both verbal and written.
  • Ability to work collaboratively in a multidisciplinary and international team environment.

Our offer

  • As a PhD candidate at UT, you will be appointed to a full-time position for four years within a very stimulating and exciting scientific environment.
  • The University offers a dynamic ecosystem with enthusiastic colleagues.
  • Your salary and associated conditions are in accordance with the collective labor agreement for Dutch universities (CAO-NU).
  • You will receive a gross monthly salary ranging from € 2.901,- (first year) up to € 3.707,- (fourth year).
  • There are excellent benefits including a holiday allowance of 8% and an end-of-year bonus of 8.3%, both of the gross annual salary.
  • a solid pension scheme.
  • A total of 41 holiday days per year in case of full-time employment
  • Free access to sports facilities on campus.
  • A family-friendly institution that offers parental leave (both paid and unpaid)
  • You will have a training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision.
  • We encourage a high degree of responsibility and independence while collaborating with close colleagues, researchers and other staff.

Information and application

Please submit your application before June 15, 2025, using the "Apply now" button, and include the following:

  • Curriculum vitae
  • Letter of motivation
  • Transcripts from your BSc and MSc courses
  • IELTS or TOEFL score
  • Contact information of 2 references

For more information, you can contact Dr. habil Celal Soyarslan via phone: +31 5 3489 7499 or email: [email protected]

About the organisation

The Faculty of Engineering Technology (ET) engages in education and research of Mechanical Engineering, Civil Engineering and Industrial Design Engineering. We enable society and industry to innovate and create value using efficient, solid and sustainable technology. We are part of a ‘people-first' university of technology, taking our place as an internationally leading center for smart production, processes and devices in five domains: Health Technology, Maintenance, Smart Regions, Smart Industry and Sustainable Resources. Our faculty is home to about 2,900 Bachelor's and Master's students, 550 employees and 150 PhD candidates. Our educational and research programmes are closely connected with UT research institutes Mesa+ Institute, TechMed Center and Digital Society Institute.

Informatie over de vacature

Functienaam
PhD Position: Improved Temper Roll-Force Prediction Through Microstructural Modelling
Locatie
Drienerlolaan 5 Enschede, Nederland
Gepubliceerd
2025-05-22
Uiterste sollicitatiedatum
2025-06-15 23:59 (Europe/Amsterdam)
2025-06-15 23:59 (CET)
Soort functie
PhD
Baan opslaan

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