Zobrazeno 1 - 10 of 54 pro vyhledávání: '"D. Hochhalter"'
1
Interpretable Machine Learning for Texture-Dependent Constitutive Models with Automatic Code Generation for Topological Optimization
Autor: Karl Garbrecht, Anthony D. Rollett, Allen Sanderson, Robert M. Kirby, Jacob D. Hochhalter, Miguel A. Aguilo
Publikováno v: Integrating Materials and Manufacturing Innovation. 10:373-392
Genetic programming-based symbolic regression (GPSR) is a machine learning method which produces symbolic models that can be readily interpreted. This study utilized GPSR to derive uniaxial texture-based constitutive models for an additively manufact
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7d670a2336ac06406b994ce6e9377389
https://doi.org/10.1007/s40192-021-00231-6
Zobrazit plný text záznamu
2
Akademický článek
A Computationally-Efficient Probabilistic Approach to Model-Based Damage Diagnosis
Autor: James E. Warner, Geoffrey F. Bomarito, Jacob D. Hochhalter, William P. Leser, Patrick E. Leser, John A. Newman
Publikováno v: International Journal of Prognostics and Health Management, Vol 8, Iss 2 (2017)
This work presents a computationally-efficient, probabilistic approach to model-based damage diagnosis. Given measurement data, probability distributions of unknown damage parameters are estimated using Bayesian inference and Markov chain Monte Carlo
Externí odkaz: https://doaj.org/article/555c567dae0b48db9da296cce83d20b1
Zobrazit plný text záznamu
5
A Computationally-Efficient Probabilistic Approach to Model-Based Damage Diagnosis
Autor: James E, Warner, Geoffrey F, Bomarito, Jacob D, Hochhalter, William P, Leser, Patrick E, Leser, John A, Newman
Publikováno v: International journal of prognostics and health management
This work presents a computationally-efficient, probabilistic approach to model-based damage diagnosis. Given measurement data, probability distributions of unknown damage parameters are estimated using Bayesian inference and Markov chain Monte Carlo
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::8e1900bd194819cd0da8b8f76fbdb8a7
https://pubmed.ncbi.nlm.nih.gov/32704401
Zobrazit plný text záznamu
6
Non-deterministic Calibration of Crystal Plasticity Model Parameters
Autor: James E. Warner, Patrick E. Leser, G.F. Bomarito, Saikumar R. Yeratapally, William P. Leser, Jacob D. Hochhalter, T.J. Ruggles
Publikováno v: Integrated Computational Materials Engineering (ICME) ISBN: 9783030405618
Crystal plasticity constitutive models are frequently used with finite elements for modeling metallic grain-scale phenomena. The accuracy of these models is directly a function of the calibrated parameters, which fully define a crystal plasticity mod
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d6f7673878a467e1f8c3165255ec30c1
https://doi.org/10.1007/978-3-030-40562-5_6
Zobrazit plný text záznamu
7
Data-Driven Correlation Analysis Between Observed 3D Fatigue-Crack Path and Computed Fields from High-Fidelity, Crystal-Plasticity, Finite-Element Simulations
Autor: Jacob D. Hochhalter, Ashley D. Spear, Kyle D. Pierson
Publikováno v: JOM. 70:1159-1167
Systematic correlation analysis was performed between simulated micromechanical fields in an uncracked polycrystal and the known path of an eventual fatigue-crack surface based on experimental observation. Concurrent multiscale finite-element simulat
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5ce67cbbfae7c29354d1a6b548e651cb
https://doi.org/10.1007/s11837-018-2884-2
Zobrazit plný text záznamu
8
Development of interpretable, data-driven plasticity models with symbolic regression
Autor: K.M. Stewart, Kathryn Esham, G.F. Bomarito, T.S. Townsend, Jacob D. Hochhalter, John M Emery
Publikováno v: Computers & Structures. 252:106557
In many applications, such as those which drive new material discovery, constitutive models are sought that have three characteristics: (1) the ability to be derived in automatic fashion with (2) high accuracy and (3) an interpretable nature. Traditi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2e05070e00bf24c0bf8b627a40a3aef1
https://doi.org/10.1016/j.compstruc.2021.106557
Zobrazit plný text záznamu
9
Selectively Electron-Transparent Microstamping Toward Concurrent Digital Image Correlation and High-Angular Resolution Electron Backscatter Diffraction (EBSD) Analysis
Autor: Jacob D. Hochhalter, G.F. Bomarito, Andrew H. Cannon, T.J. Ruggles
Publikováno v: Microscopy and Microanalysis. 23:1091-1095
Digital image correlation (DIC) in a scanning electron microscope and high-angular resolution electron backscatter diffraction (HREBSD) provide valuable and complementary data concerning local deformation at the microscale. However, standard surface
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bd672045911aa259e46b617c0148680f
https://doi.org/10.1017/s1431927617012703
Zobrazit plný text záznamu
10
Development of Optimal Multiscale Patterns for Digital Image Correlation via Local Grayscale Variation
Autor: G.F. Bomarito, Jacob D. Hochhalter, T.J. Ruggles
Publikováno v: Experimental Mechanics. 58:1169-1180
In many applications of digital image correlation (DIC), it is advantageous to have measurements at multiple scales. Because it is rare to have natural features that can be used for DIC at multiple magnifications, an appropriately multiscale DIC patt
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ffd01a38ae7d1f9133aed49f805ad978
https://doi.org/10.1007/s11340-017-0348-1
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje