About

George N. Frantziskonis is a Professor of Civil Engineering and Engineering Mechanics at the University of Arizona, with a courtesy appointment in the Material Science and Engineering Department. He received his civil engineering degree from Aristotle University in Greece in 1982 and his doctorate in engineering mechanics from the University of Arizona in 1986. He joined the university faculty in 1988 after a visiting position at Aristotle University and consulting for industry. His research interests encompass multi- and inter-disciplinary multiscale modeling, simulation, and experimentation, with applications in material characterization, probabilistic and multiscale problem formulation, behavior of materials at nano-scale, reaction-diffusion-transport phenomena, and smart materials across various scales. He has published extensively across multiple scientific journals, extending multiscale methods to diverse areas of science and engineering, including mechanics, physics, civil, mechanical, aerospace, materials science, chemical engineering, and computational physics. Frantziskonis has worked internationally as a visiting professor in France, Norway, and Greece, and has taught courses in France and Germany. He has also worked at Department of Defense laboratories and received awards such as the NSF Presidential Young Investigator and Fulbright Scholar awards.

Research topics

• Computer Science
• Materials science
• Mechanical engineering
• Composite material
• Structural engineering
• Engineering
• Physics
• Mathematics
• Chemistry
• Geometry

Selected publications

• Machine Learning of Impact Behavior in Cold Spray of Similar and Dissimilar Metals

  Integrating materials and manufacturing innovation · 2025-09-01 · 1 citations

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• Atomistic characterization of impact bonding in cold spray deposition of copper

  Materialia · 2023-03-05 · 11 citations

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• Atomistic Characterization of Impact Bonding in Cold Spray Deposition of Copper

  SSRN Electronic Journal · 2022-01-01

  articleOpen access
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• Development of statistical models for porosity from digital optical micrographs with application to metal additive manufacturing microstructure

  Computational Materials Science · 2022-01-06 · 6 citations

  articleSenior authorCorresponding
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• A partition and microstructure based method applicable to large-scale topology optimization

  Mechanics of Materials · 2022-01-21 · 9 citations

  articleSenior authorCorresponding
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• Reliability of metal additive manufactured materials from modeling the microstructure at different length scales

  Additive manufacturing · 2022 · 10 citations

  Senior authorCorresponding
  • Computer Science
  • Mechanical engineering
  • Materials science
  PublisherDOI

• Techno-economic assessment and design optimization of compressed air energy storage using filament wound carbon fiber reinforced plastic pressure vessels

  Journal of Energy Storage · 2021 · 20 citations

  Senior authorCorresponding
  • Computer Science
  • Materials science
  • Structural engineering
  PublisherDOI

• Design of porous and graded NiTi smart energy absorbers considering synthetic uncertainty in parameters

  Journal of Intelligent Material Systems and Structures · 2020-12-10 · 6 citations

  articleSenior authorCorresponding

  The synthetic uncertainty (SU) method is introduced and applied to the optimal design of energy absorbing NiTi shape memory alloy (SMA) bars. A sensitivity analysis for a large number of stochastic parameters identifies geometrical grading, porosity, and imposed maximum nominal stress as critical design parameters for the energy dissipation capacity of the bars. Parametric uncertainty on the optimal design of the energy absorber is incorporated and estimated through the SU formalism. The SU method provides a unified approach to discover the critical design parameters, quantify uncertainty, and optimally design a system around its extreme response (maximum or minimum). Therefore, the SU method is placed next to the robust design optimization (RDO) process, yet with a discovery component. It is found that variations in porosity and shape factor can significantly alter the stress-strain response and energy dissipation capacity. For a given value of maximum nominal stress, it is found that there exists an optimal combination of shape factor and porosity which maximizes the energy dissipation capacity of a tapered and porous NiTi bar.

  PublisherDOI

• From atomic-scale to mesoscale: A characterization of geopolymer composites using molecular dynamics and peridynamics simulations

  Computational Materials Science · 2020 · 21 citations

  • Materials science
  • Composite material
  • Chemistry
  PublisherDOI

• The effect of grain-size on fracture of polycrystalline silicon carbide: A multiscale analysis using a molecular dynamics-peridynamics framework

  Computational Materials Science · 2018-12-22 · 37 citations

  articleCorresponding
  PublisherDOI

Frequent coauthors

• Krishna Muralidharan

  19 shared

• Sreekanth Pannala

  Saudi Arabia Basic Industries (United States)

  15 shared

• C. S. Desai

  University of Arizona

  13 shared

• Srdjan Simunovic

  Oak Ridge National Laboratory

  13 shared

• Sourav Gur

  Indian Institute of Technology Patna

  13 shared

• Pierre A. Deymier

  University of Arizona

  12 shared

• Sudib Kumar Mishra

  Indian Institute of Technology Kanpur

  10 shared

• Markos Avlonitis

  Ionian University

  10 shared

Awards & honors

• NSF Presidential Young Investigator award
• Fulbright Scholar award