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Classification of Systems-II01:31

Classification of Systems-II

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Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
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Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
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Materials Knowledge Systems in Python - A Data Science Framework for Accelerated Development of Hierarchical

David B Brough1, Daniel Wheeler2, Surya R Kalidindi1,3

  • 1School of Computational Science and Engineering, Georgia Institute of Technology, 30332, Atlanta, USA.

Integrating Materials and Manufacturing Innovation
|July 11, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces PyMKS, an open-source framework for materials data science. It enables the creation of Process-Structure-Property (PSP) linkages for hierarchical materials, facilitating knowledge transfer in materials science and engineering.

Keywords:
Hierarchical MaterialsMachine LearningMaterials Knowledge SystemsMultiscale MaterialsNumPyPythonSciPyScikit-learn

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Area of Science:

  • Materials Science and Engineering
  • Data Science
  • Computational Materials Science

Background:

  • There is a critical need for advanced analytical methods to understand the stochastic nature of material structures across multiple length scales.
  • Extracting relevant and transferable knowledge from complex material data is essential for innovation.
  • Data-driven Process-Structure-Property (PSP) linkages offer a framework for curating and transferring materials knowledge.

Purpose of the Study:

  • To introduce the Materials Knowledge Systems in Python (PyMKS) project, an open-source framework.
  • To demonstrate the creation of high-value PSP linkages for hierarchical materials.
  • To facilitate the use and refinement of these linkages by diverse research communities.

Main Methods:

  • Development of an open-source Python framework (PyMKS) for materials data science.
  • Implementation of functionalities for creating data-driven PSP linkages.
  • Utilizing hierarchical frameworks to manage complex material data.

Main Results:

  • PyMKS provides a systemic, modular, and hierarchical framework for materials knowledge.
  • The framework enables the development of transferable PSP linkages.
  • The paper illustrates the accessibility and utilization of PyMKS functions.

Conclusions:

  • PyMKS is the first open-source framework for creating PSP linkages for hierarchical materials.
  • The framework empowers materials science, engineering, manufacturing, and data science experts.
  • PyMKS promotes community-driven curation and transference of materials knowledge.