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Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
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Published on: December 13, 2016

Cooperative modelling and design on the computing grid: data, flux and knowledge interoperability.

Antonio Laganà1, Elda Rossi, Stefano Evangelisti

  • 1Dipartimento di Chimica, Università di Perugia, Perugia, Italy, lagana05@gmail.com.

Journal of Molecular Modeling
|April 27, 2013
PubMed
Summary

Scientists are using distributed platforms and grid-empowered molecular simulators to tackle complex problems in molecular science. This approach standardizes data, bridges high-throughput and high-performance computing, and rewards collaborative research efforts.

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Area of Science:

  • Molecular and Materials Science and Technologies
  • Computational Chemistry
  • Scientific Computing

Background:

  • Distributed computing platforms enable complex problem-solving through software chaining.
  • Grid-empowered molecular simulators integrate expertise from theorists and experimentalists.
  • This collaborative approach is crucial for advancing molecular and materials science.

Purpose of the Study:

  • To report on the development and impact of grid-empowered molecular simulators.
  • To highlight advancements in data standardization and virtual experiment design.
  • To introduce tools for evaluating collaborative research quality and rewarding contributions.

Main Methods:

  • Chaining specialized software on distributed platforms.
  • Combining expertise in electronic structure and nuclei dynamics.
  • Developing standardized data formats and virtual experiment frameworks.

Main Results:

  • Unprecedented data format standardization achieved.
  • Successful bridging of high-throughput and high-performance computing platforms.
  • Development of tools for assessing collaborative effort and implementing credit economies.

Conclusions:

  • Grid-empowered molecular simulators facilitate complex scientific endeavors.
  • Standardization and collaborative tools enhance research quality and community engagement.
  • This approach fosters a rewarding ecosystem for scientific cooperation.