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Case Study

Ansys + NMITE

“Ansys Granta EduPack has been invaluable for students and teaching alike. It has supported them in selecting materials confidently and proficiently. The comprehensive and flexible database allows students to not only include the materials’ properties in the analysis and selection process, but also the processing and environmental impact properties. Ansys Granta EduPack is a brilliant tool!” 

— Aris Quintana-Nedelcos PH.D, FHEA  Assitant Professor / 3D The New Model Institute for Technology & Engineering (NMITE)

Introduction

Appropriate materials selection for a specific application can be a daunting task. When aiming to identify “the best material,” a rigorous analytical process is often required, necessitating compromises in certain areas. To ensure students are prepared to tackle these issues, it is vital to provide them with a tool that allows them to be trained in the analytical process with a comprehensive materials dataset. Doing so in the most efficient way is paramount to their professional training. To better support students in their training in material selection for specific applications, we need to give them access to a large library of materials’ datasheets. They should be able to filter for specific properties and range, and compare the top selections in a flexible way. The ability to export the materials profile to simulation packages for further analysis is also important.

Engineering Solution

Granta Edupack is particularly attractive for NMITE for the following reasons:

  • Comprehensive database of materials datasheets
  • Flexible usage options that enable a variety of different analysis
  • The ability to include not only the material’s properties but also its processing and environmental impact properties in the analysis and selection process  

Benefits

  • The size, richness and flexibility of the database enables NMITE to focus on the most critical aspects of the materials selection analytical process
  • Emphasis on the anaytical process
  • Student confidence when using a large database 

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