Master Thesis stress-time histories (m/w/d)

Allgemeine Informationen

Legaleinheit

Framatome ist ein international führender Hersteller in der kerntechnischen Industrie. Dank seiner internationalen Expertise, der durchgängig hohen Qualität der Lösungen sowie innovativer Technologien genießt das Unternehmen seit vielen Jahren einen ausgezeichneten Ruf und steht für Zuverlässigkeit und exzellente Leistung. Auf dieser Basis entwickelt, fertigt und installiert Framatome Komponenten und Brennstoffe sowie Leittechniksysteme für Kernkraftwerke und bietet umfassende Serviceleistungen für Reaktoren. Rund 15.000 Mitarbeiterinnen und Mitarbeiter in aller Welt tragen jeden Tag dazu bei, die Sicherheit und Wirtschaftlichkeit kerntechnischer Anlagen stetig weiter zu verbessern, um sauberen, bezahlbaren und mit geringem Kohlenstoffausstoß erzeugten Strom bereitzustellen. Besuchen Sie uns auf www.framatome.com und folgen Sie uns auf Twitter: @Framatome_ und LinkedIn: Framatome.
Die Anteile an Framatome halten EDF (75,5 Prozent), Mitsubishi Heavy Industries (19,5 Prozent) und Assystem (5 Prozent).

Kennziffer

2024-16718  

Datum der Veröffentlichung

05.04.2024

Beschreibung der Stelle

Berufsfeld

R - RESEARCH & DEVELOPMENT - R1 - F&E-Management

Stellentitel

Master Thesis stress-time histories (m/w/d)

Vertragsart

Praktikum & Abschlussarbeit

Aufgabenbeschreibung

„Determination of temperature and stress-time histories for thermally loaded pipes“

Your work will contribute to the determination of stress-time histories for thermo-mechanical piping loads.

Contents of the master thesis (topic) are as follows:

Framatome disposes of decades of experience in the fatigue monitoring of power plant components based on the local measurement of the operational thermo-mechanical loads. The methods are subject to permanent amendment, improvement and development.

The load measurements can be based on thermocouples arranged in measurement sections which are attached to the outer wall of the pipe, on displacements or – as part of latest development efforts – on electromagnetic transducers (EMAT’s). Although the load measurement is fairly local there is always the task of transferring the load information to the location of interest (i.e. the location of potential fatigue damage) and at least to the inner wall of the pipe. Subsequently, the stress-time-history of the complete stress tensor at the relevant location has to be derived and is used for rainflow cycle counting and calcu­lation of partial and cumulative fatigue usage factors (CUF’s). The speed of execution is another related topic and subject of Framatome’s Fast Fatigue Evaluation (FFE) solution. 

The work will emanate from a comprehensive literature study including the latest published research and development results of local fatigue monitoring. Based on the acquired knowledge a solution for the de­termination of inner wall temperatures, displacements and stresses is to be developed. Input data are available information on outer wall and / or mean wall temperatures and / or displacements. The analyti­cal solution with Bessel’s functions of Albrecht [1] is to be taken explicitly into account. Furthermore, arti­ficial intelligence (AI) approaches for supporting the problem solution have to be checked. The proposed solution is to be implemented in a well documented, quality controlled and further usable software (Py­thon). The speed of execution is to be proven. For validation purposes the available results of measure­ments at a pipe test rig subjected to different defined thermal transients are to be used. The applicability for fast transients is to be shown in particular.

Proposals of integrating the established solution into the existing fatigue assessment modules are to be made.

All steps have to be specified and documented. Further proposals for improvement should be made. The final thesis will meet the requirements of integrating the module in the existing fatigue monitoring system.

Anforderungen

• highly motivated student of mechanical engineering, technical mechanics or maths
• fluent in English
• basic knowledge of thermodynamics and strength of materials
• advanced knowledge of analytical and numerical mathematics
• independent, structured and purposeful work under regular supervision
• basic knowledge of Finite Element Method (ANSYS)
• solid knowledge of technical software development (Python)

Regelmäßige Arbeitszeit

Vollzeit

Einsatzort der Stelle

Arbeitsort

Deutschland, Bayern - Erlangen, Erlangen

Erste Tätigkeitsstätte

Erlangen

Stellenkategorie

Standard

Qualifikation

Höchster Bildungsabschluss

Abitur

Berufserfahrung

In Ausbildung / Berufseinstieg