Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques

Romanov, Vyacheslav; Hawk, Jeffrey A.; Krishnamurthy, Narayanan; Maddali, Siddharth

Title: Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques

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Authors:

Romanov, Vyacheslav; Hawk, Jeffrey A.; Krishnamurthy, Narayanan ^[1]; Maddali, Siddharth ^[1]

Foreign National

Publication Date:: Sun Mar 12 00:00:00 EST 2017

Research Org.:: National Energy Technology Lab. (NETL), Pittsburgh, PA, and Morgantown, WV (United States). In-house Research

Sponsoring Org.:: USDOE Office of Fossil Energy (FE)

OSTI Identifier:: 1413205

Report Number(s):: NETL-PUB-20885

Resource Type:: Conference

Resource Relation:: Conference: APS March Meeting 2017, New Orleans, LA, March 13-17, 2017.

Country of Publication:: United States

Language:: English

Subject:: 20 FOSSIL-FUELED POWER PLANTS; 36 MATERIALS SCIENCE; 42 ENGINEERING; 97 MATHEMATICS AND COMPUTING; Machine Learning, steel alloys, mechanical properties

Citation Formats


                    Romanov, Vyacheslav, Hawk, Jeffrey A., Krishnamurthy, Narayanan, and Maddali, Siddharth. Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques.  United States: N. p., 2017. 
        Web.

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                    Romanov, Vyacheslav, Hawk, Jeffrey A., Krishnamurthy, Narayanan, & Maddali, Siddharth. Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques.  United States.

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                    Romanov, Vyacheslav, Hawk, Jeffrey A., Krishnamurthy, Narayanan, and Maddali, Siddharth. 2017.  
        "Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques".  United States.  https://www.osti.gov/servlets/purl/1413205.

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@article{osti_1413205,

  title        = {Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques},

  author       = {Romanov, Vyacheslav and Hawk, Jeffrey A. and Krishnamurthy, Narayanan and Maddali, Siddharth},

  abstractNote = {},

  doi          = {},

  url          = {https://www.osti.gov/biblio/1413205},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sun Mar 12 00:00:00 EST 2017},

  month        = {Sun Mar 12 00:00:00 EST 2017}

}

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