scholarly journals Cloud-Based ICME Software Training

2020 ◽  
Vol 11 (1) ◽  
pp. 5
Author(s):  
Lukas Koschmieder ◽  
Ralph Altenfeld ◽  
Janin Eiken ◽  
Bernd Böttger ◽  
Georg J. Schmitz
Keyword(s):  
Online Training ◽  
Simulation Software ◽  
Simulation Tools ◽  
Materials Engineering ◽  
Integrated Computational Materials Engineering ◽  
Hands On ◽  
Training Event ◽  
Training Courses ◽  
Computational Materials ◽  
Practical Experiences

Hands-on type training of Integrated Computational Materials Engineering (ICME) is characterized by assisted application and combination of multiple simulation software tools and data. In this paper, we present recent experiences in establishing a cloud-based infrastructure to enable remote use of dedicated commercial and open access simulation tools during an interactive online training event. In the first part, we summarize the hardware and software requirements and illustrate how these have been met using cloud hardware services, a simulation platform environment, a suitable communication channel, common workspaces, and more. The second part of the article focuses (i) on the requirements for suitable online hands-on training material and (ii) on details of some of the approaches taken. Eventually, the practical experiences gained during three consecutive online training courses held in September 2020 with 35 nominal participants each, are discussed in detail.

scholarly journals Cloud-Based ICME Software Training

2020 ◽  
Author(s):  
Lukas Koschmieder ◽  
Ralph Altenfeld ◽  
Janin Eiken ◽  
Bernd Böttger ◽  
Georg J. Schmitz
Keyword(s):  
Simulation Software ◽  
Simulation Tools ◽  
Materials Engineering ◽  
Integrated Computational Materials Engineering ◽  
Hands On ◽  
Training Event ◽  
On Line ◽  
Training Courses ◽  
Computational Materials ◽  
Practical Experiences

Hands-on type training of Integrated Computational Materials Engineering (ICME) is characterized by assisted application and combination of multiple simulation software tools and data. In this paper, we present recent experiences in establishing a cloud-based infrastructure to enable remote use of dedicated commercial and open access simulation tools during an interactive on-line training event. In the first part, we summarize the hardware and software requirements and illustrate how these have been met using cloud hardware services, a simulation platform environment, a suitable communication channel, common workspaces and more. The second part of the article focuses (i) on the requirements for suitable on-line hands-on training material and (ii) on details of some of the approaches taken. Eventually, the practical experiences made during three consecutive on-line training courses held in September 2020 with 35 nominal participants each, are discussed in detail.

Optimization of Magnesium Alloy Casting Process: An Integrated Computational Materials Engineering (ICME) Approach

2021 ◽  
Vol 1035 ◽  
pp. 808-812
Author(s):  
Xing Yang Chang ◽  
Qi Shen ◽  
Wen Xue Fan ◽  
Hai Hao
Keyword(s):  
Magnesium Alloy ◽  
Process Optimization ◽  
Casting Process ◽  
Mold Temperature ◽  
Pressure Casting ◽  
Alloy Casting ◽  
Materials Engineering ◽  
Integrated Computational Materials Engineering ◽  
Computational Materials ◽  
Low Efficiency

Traditional casting process optimization usually adopts empirical trial and error method. Process parameters were modified repeatedly within a certain range until a satisfactory solution is obtained, which is costly and inefficient. Therefore, based on integrated computational materials engineering, Magnesium Alloy Simulation Integrated Platform (MASIP) was constructed. MASIP completed the automatic operation of the entire simulation process from the CAD model data input to the process-microstructure-performance. It realized the rapid optimization simulation prediction of process-microstructure-performance, and solved the problems of long cycle and low efficiency of traditional process optimization. This paper studied the low-pressure casting optimization process of magnesium alloy thin-walled cylindrical parts based on MASIP. The calculation took casting temperature, mold temperature and holding pressure as the optimized variables, and the yield strength of the casting as the target variable. The experimental results showed that MASIP can fairly complete the structure simulation and performance prediction of castings, greatly reduce the time cost of the calculation process, and improve the efficiency of process optimization.

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