Daniel Thomas Seidl

Sandia National Laboratories

*This is an algorithmically generated author record based on publicly available information.

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Sandia National Laboratories

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Daniel Thomas Seidl has a total of 85 co-authors. Here are the top co-authors by number of shared publications:

Usdoe National Nuclear Security Administration (Nnsa)
19 shared publications
Reese Edward Jones
Sandia National Laboratories
18 shared publications
Albuquerque Sandia National Laboratories (Snl-Nm)
17 shared publications
Brian Neal Granzow
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
14 shared publications
Jan Fuhg
University of Texas at Austin
8 shared publications
Elizabeth M. C. Jones
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
6 shared publications

Latest Publications

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- 1 September 2026
- Published by Office of Scientific and Technical Information (OSTI)
A Hybrid Approach to Constitutive Model Discovery for Coupled Physics via Multi-modal Data Fusion
by Usdoe National Nuclear Security Administration (Nnsa), Daniel Seidl, Albuquerque Sandia National Laboratories (Snl-Nm), Brian Granzow, Ravi Patel, Reese Jones
Website
Google Scholar
- 1 September 2026
- Published by Office of Scientific and Technical Information (OSTI)
A Hybrid Approach to Constitutive Model Discovery for Coupled Physics via Multi-modal Data Fusion
by Usdoe National Nuclear Security Administration (Nnsa), Daniel Seidl, Albuquerque Sandia National Laboratories (Snl-Nm), Brian Granzow, Ravi Patel, Reese Jones
Website
Google Scholar
- 10 August 2026
- Published by Elsevier in Computer Methods in Applied Mechanics and Engineering
Multiscale topology optimization of compressible and nearly incompressible anisotropic hyperelastic structures using physics-augmented neural networks
by Asghar A. Jadoon, Aryan Tyagi, L. River Spencer, Reese E. Jones, Manuel K. Rausch, Ryan Alberdi, D. Thomas Seidl, Jan N. Fuhg
Website
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- 10 August 2026
- Published by Elsevier in Computer Methods in Applied Mechanics and Engineering
Multiscale topology optimization of compressible and nearly incompressible anisotropic hyperelastic structures using physics-augmented neural networks
by Asghar A. Jadoon, Aryan Tyagi, L. River Spencer, Reese E. Jones, Manuel K. Rausch, Ryan Alberdi, D. Thomas Seidl, Jan N. Fuhg
Website
Google Scholar
Cited by 2
- 19 June 2026
- Published by Elsevier in International Journal of Solids and Structures
Thermodynamically consistent hybrid and permutation-invariant neural yield functions for anisotropic plasticity
by Asghar A. Jadoon, Ravi G. Patel, Brian N. Granzow, Reese E. Jones, D. Thomas Seidl, Jan N. Fuhg
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- 19 June 2026
- Published by Elsevier in International Journal of Solids and Structures
Thermodynamically consistent hybrid and permutation-invariant neural yield functions for anisotropic plasticity
by Asghar A. Jadoon, Ravi G. Patel, Brian N. Granzow, Reese E. Jones, D. Thomas Seidl, Jan N. Fuhg
Cited by 2
Website
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Cited by 6
- 4 April 2026
- Published by Elsevier in Computer Methods in Applied Mechanics and Engineering
A physics-augmented neural network framework for modeling and characterizing thermo-visco-plastic behavior
by Reese E. Jones, Asghar A. Jadoon, D. Thomas Seidl, Jan N. Fuhg
Website
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- 4 April 2026
- Published by Elsevier in Computer Methods in Applied Mechanics and Engineering
A physics-augmented neural network framework for modeling and characterizing thermo-visco-plastic behavior
by Reese E. Jones, Asghar A. Jadoon, D. Thomas Seidl, Jan N. Fuhg
Cited by 6
Website
Google Scholar
- 1 October 2025
- Published by Office of Scientific and Technical Information (OSTI)
Calibration of Hybrid Elastoplastic Constitutive Models from Experimental Data
by Albuquerque Sandia National Laboratories (Snl-Nm), Daniel Seidl, Usdoe National Nuclear Security Administration (Nnsa), Asghar Jadoon, Brian Granzow, Ravi Patel, Reese Jones, Jan Fuhg
Website
Google Scholar
- 1 October 2025
- Published by Office of Scientific and Technical Information (OSTI)
Calibration of Hybrid Elastoplastic Constitutive Models from Experimental Data
by Albuquerque Sandia National Laboratories (Snl-Nm), Daniel Seidl, Usdoe National Nuclear Security Administration (Nnsa), Asghar Jadoon, Brian Granzow, Ravi Patel, Reese Jones, Jan Fuhg
Website
Google Scholar
Cited by 7
- 19 September 2025
- Published by Elsevier in International Journal of Engineering Science
Physics augmented machine learning discovery of composition-dependent constitutive laws for 3D printed digital materials
by Steven Yang, Michal Levin, Govinda Anantha Padmanabha, Miriam Borshevsky, Ohad Cohen, D. Thomas Seidl, Reese E. Jones, Nikolaos Bouklas, Noy Cohen
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- 19 September 2025
- Published by Elsevier in International Journal of Engineering Science
Physics augmented machine learning discovery of composition-dependent constitutive laws for 3D printed digital materials
by Steven Yang, Michal Levin, Govinda Anantha Padmanabha, Miriam Borshevsky, Ohad Cohen, D. Thomas Seidl, Reese E. Jones, Nikolaos Bouklas, Noy Cohen
Cited by 7
Website
Google Scholar
- 2 September 2025
- Published by Elsevier in Applied Mathematics Letters
A note on the reliability of goal-oriented error estimates for Galerkin finite element methods with nonlinear functionals
by Brian N. Granzow, Stephen D. Bond, D. Thomas Seidl, Bernhard Endtmayer
Website
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- 2 September 2025
- Published by Elsevier in Applied Mathematics Letters
A note on the reliability of goal-oriented error estimates for Galerkin finite element methods with nonlinear functionals
by Brian N. Granzow, Stephen D. Bond, D. Thomas Seidl, Bernhard Endtmayer
Website
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- 1 August 2025
- Published by Office of Scientific and Technical Information (OSTI)
Machine learning constitutive models of inelastic materials with microstructure
by Livermore Sandia National Laboratories (Snl-Ca), Reese Jones, Other (Doe), Daniel Seidl, Ravi Patel, Jan Fuhg
Website
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- 1 August 2025
- Published by Office of Scientific and Technical Information (OSTI)
Machine learning constitutive models of inelastic materials with microstructure
by Livermore Sandia National Laboratories (Snl-Ca), Reese Jones, Other (Doe), Daniel Seidl, Ravi Patel, Jan Fuhg
Website
Google Scholar
- 1 July 2025
- Published by Office of Scientific and Technical Information (OSTI)
Differentiable Programming for Constitutive Model Calibration
by Albuquerque Sandia National Laboratories (Snl-Nm), Daniel Seidl, Usdoe National Nuclear Security Administration (Nnsa), Brian Granzow
Website
Google Scholar
- 1 July 2025
- Published by Office of Scientific and Technical Information (OSTI)
Differentiable Programming for Constitutive Model Calibration
by Albuquerque Sandia National Laboratories (Snl-Nm), Daniel Seidl, Usdoe National Nuclear Security Administration (Nnsa), Brian Granzow
Website
Google Scholar
- 1 July 2025
- Published by Office of Scientific and Technical Information (OSTI)
Recent extensions to physics-augmented neural networks
by Livermore Sandia National Laboratories (Snl-Ca), Jan Fuhg, Usdoe National Nuclear Security Administration (Nnsa), Asghar Jadoon, Adrian Tepole, Manuel Rausch, Reese Jones, Daniel Seidl
Website
Google Scholar
- 1 July 2025
- Published by Office of Scientific and Technical Information (OSTI)
Recent extensions to physics-augmented neural networks
by Livermore Sandia National Laboratories (Snl-Ca), Jan Fuhg, Usdoe National Nuclear Security Administration (Nnsa), Asghar Jadoon, Adrian Tepole, Manuel Rausch, Reese Jones, Daniel Seidl

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