Sökning: "Martensit"
Visar resultat 1 - 5 av 13 uppsatser innehållade ordet Martensit.
1. Influence from temperature variations in stacking fault energy on the mechanical properties of stainless steels
Kandidat-uppsats, KTH/MaterialvetenskapSammanfattning : This paper investigates the mechanical properties and deformation mechanisms of austenitic stainless steels and how they relate to the material property of stacking fault energy (SFE) and its relation to temperature and nickel content. Austenitic stainless steels are commonly used and well known for good mechanical properties and deformation characteristics. LÄS MER
2. Precipitation analysis in bearing steel Hybrid 60
Master-uppsats, KTH/MaterialvetenskapSammanfattning : New materials are always being developed to get the best properties possible where needed. The way to create these materials and test them is also developing. When it comes to high-strength steels, a martensitic microstructure is a common choice. LÄS MER
3. Simulation and Experimental Based Hardenability Evaluation of Chromium Alloyed Powder Metal Steels
Master-uppsats, KTH/MaterialvetenskapSammanfattning : Powder metallurgy is a branch of metal forming technology where metal powders are used to manufacture parts and components. It is a flexible and economical technique for manufacturing complicated shapes. This present work focuses on press and sinter technology and forms a part of Höganäs’s efforts of modelling hardenability through quenching. LÄS MER
4. Undersökning av induktionshärdning för automatiserad processtyrning
Master-uppsats, KTH/Industriell produktionSammanfattning : Denna rapport granskar hur härdzonen hos vevaxlar påverkas av ändrade processparametrar i induktionshärdningsprocessen. Uppvärmningsdelen av härdningsprocessen har studerats med en infraröd värmekamera för att se hur temperaturkurvorna varierar när processparametrar ändras. LÄS MER
5. Combined CALPHAD and Machine Learning for Property Modelling
Master-uppsats, KTH/MaterialvetenskapSammanfattning : Techniques to improve the speed at which materials are researched and developed has been conducted by investigating the machine learning methodology. These techniques offer solutions to connect the length scales of material prop- erties from atomistic and chemical features using materials databases generated from collected data. LÄS MER