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You searched for +publisher:"Georgia Tech" +contributor:("Saldana, Christopher"). Showing records 1 – 16 of 16 total matches.

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Georgia Tech

1. Qiao, Haipeng. Understanding subsurface integrity in machining of cellular solids.

Degree: MS, Mechanical Engineering, 2017, Georgia Tech

 Thermomechanical loading during surface severe plastic deformation in machining is marked by the generation of high and graded strains, strain rates and temperatures in bulk… (more)

Subjects/Keywords: Foams; Cellular solid; Tomography; Digital volume correlation; Watershed segmentation

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APA (6th Edition):

Qiao, H. (2017). Understanding subsurface integrity in machining of cellular solids. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60178

Chicago Manual of Style (16th Edition):

Qiao, Haipeng. “Understanding subsurface integrity in machining of cellular solids.” 2017. Masters Thesis, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/60178.

MLA Handbook (7th Edition):

Qiao, Haipeng. “Understanding subsurface integrity in machining of cellular solids.” 2017. Web. 19 Mar 2019.

Vancouver:

Qiao H. Understanding subsurface integrity in machining of cellular solids. [Internet] [Masters thesis]. Georgia Tech; 2017. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/60178.

Council of Science Editors:

Qiao H. Understanding subsurface integrity in machining of cellular solids. [Masters Thesis]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/60178


Georgia Tech

2. Praniewicz, Maxwell R. Adaptive geometry transformation and repair methodology for hybrid manufacturing.

Degree: MS, Mechanical Engineering, 2018, Georgia Tech

 With hybrid manufacturing maturing into a commercial scale, industries are pushing to integrate and fully utilize this new technology in their production facilities. Using the… (more)

Subjects/Keywords: Hybrid manufacturing; Registration; Model adaptation; Adaptive machining

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APA (6th Edition):

Praniewicz, M. R. (2018). Adaptive geometry transformation and repair methodology for hybrid manufacturing. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60215

Chicago Manual of Style (16th Edition):

Praniewicz, Maxwell R. “Adaptive geometry transformation and repair methodology for hybrid manufacturing.” 2018. Masters Thesis, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/60215.

MLA Handbook (7th Edition):

Praniewicz, Maxwell R. “Adaptive geometry transformation and repair methodology for hybrid manufacturing.” 2018. Web. 19 Mar 2019.

Vancouver:

Praniewicz MR. Adaptive geometry transformation and repair methodology for hybrid manufacturing. [Internet] [Masters thesis]. Georgia Tech; 2018. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/60215.

Council of Science Editors:

Praniewicz MR. Adaptive geometry transformation and repair methodology for hybrid manufacturing. [Masters Thesis]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60215


Georgia Tech

3. Srinivasan, Nishant. Process development for the production of optically transparent micro-features.

Degree: MS, Mechanical Engineering, 2015, Georgia Tech

 The emergence of biofluidics devices and "Lab-on-a-Chip" testing platforms has resulted in a need for the low cost production of optically transparent micro-features. The goal… (more)

Subjects/Keywords: Process development; Micromachining; Optically transparent; Biofluidics; Low cost prototyping

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APA (6th Edition):

Srinivasan, N. (2015). Process development for the production of optically transparent micro-features. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55484

Chicago Manual of Style (16th Edition):

Srinivasan, Nishant. “Process development for the production of optically transparent micro-features.” 2015. Masters Thesis, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/55484.

MLA Handbook (7th Edition):

Srinivasan, Nishant. “Process development for the production of optically transparent micro-features.” 2015. Web. 19 Mar 2019.

Vancouver:

Srinivasan N. Process development for the production of optically transparent micro-features. [Internet] [Masters thesis]. Georgia Tech; 2015. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/55484.

Council of Science Editors:

Srinivasan N. Process development for the production of optically transparent micro-features. [Masters Thesis]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/55484


Georgia Tech

4. Parto Dezfouli, Mahmoud. A secure MTConnect compatible IoT platform for machine monitoring through integration of fog computing, cloud computing, and communication protocols.

Degree: MS, Mechanical Engineering, 2017, Georgia Tech

 Industry 4.0 aims at utilizing advancing computational frameworks such as Human-Computer Interaction and Machine Learning in traditional areas of manufacturing and production. Smart Manufacturing (SM)… (more)

Subjects/Keywords: Smart manufacturing; Internet of things; IoT; Industry 4.0; Cyber-physical systems; Fog computing; Cloud computing; Security; MTConenct; REST; HTTP; MQTT; AWS; OEE

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APA (6th Edition):

Parto Dezfouli, M. (2017). A secure MTConnect compatible IoT platform for machine monitoring through integration of fog computing, cloud computing, and communication protocols. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59283

Chicago Manual of Style (16th Edition):

Parto Dezfouli, Mahmoud. “A secure MTConnect compatible IoT platform for machine monitoring through integration of fog computing, cloud computing, and communication protocols.” 2017. Masters Thesis, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/59283.

MLA Handbook (7th Edition):

Parto Dezfouli, Mahmoud. “A secure MTConnect compatible IoT platform for machine monitoring through integration of fog computing, cloud computing, and communication protocols.” 2017. Web. 19 Mar 2019.

Vancouver:

Parto Dezfouli M. A secure MTConnect compatible IoT platform for machine monitoring through integration of fog computing, cloud computing, and communication protocols. [Internet] [Masters thesis]. Georgia Tech; 2017. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/59283.

Council of Science Editors:

Parto Dezfouli M. A secure MTConnect compatible IoT platform for machine monitoring through integration of fog computing, cloud computing, and communication protocols. [Masters Thesis]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59283


Georgia Tech

5. Ameur, Amir. Voxel-based tool sequence optimization for 5-axis machining using high performance computing.

Degree: MS, Mechanical Engineering, 2017, Georgia Tech

 This thesis presents an approach for tool sequence optimization in the case of 5-axis machining. Most of the reported work suggests tooling optimization methods involving… (more)

Subjects/Keywords: Voxels; GPU; 5-axis machining; Tool selection

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APA (6th Edition):

Ameur, A. (2017). Voxel-based tool sequence optimization for 5-axis machining using high performance computing. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60655

Chicago Manual of Style (16th Edition):

Ameur, Amir. “Voxel-based tool sequence optimization for 5-axis machining using high performance computing.” 2017. Masters Thesis, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/60655.

MLA Handbook (7th Edition):

Ameur, Amir. “Voxel-based tool sequence optimization for 5-axis machining using high performance computing.” 2017. Web. 19 Mar 2019.

Vancouver:

Ameur A. Voxel-based tool sequence optimization for 5-axis machining using high performance computing. [Internet] [Masters thesis]. Georgia Tech; 2017. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/60655.

Council of Science Editors:

Ameur A. Voxel-based tool sequence optimization for 5-axis machining using high performance computing. [Masters Thesis]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/60655


Georgia Tech

6. Pan, Zhipeng. Predictive modeling for material microstructure affected machining.

Degree: PhD, Mechanical Engineering, 2018, Georgia Tech

 The precision machining has long been focused on the machined part geometrical consideration, such as dimensional accuracy and surface roughness. The machined part dimensional accuracy… (more)

Subjects/Keywords: Machining; Force; Residual stress; Microstructure

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APA (6th Edition):

Pan, Z. (2018). Predictive modeling for material microstructure affected machining. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59741

Chicago Manual of Style (16th Edition):

Pan, Zhipeng. “Predictive modeling for material microstructure affected machining.” 2018. Doctoral Dissertation, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/59741.

MLA Handbook (7th Edition):

Pan, Zhipeng. “Predictive modeling for material microstructure affected machining.” 2018. Web. 19 Mar 2019.

Vancouver:

Pan Z. Predictive modeling for material microstructure affected machining. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/59741.

Council of Science Editors:

Pan Z. Predictive modeling for material microstructure affected machining. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59741


Georgia Tech

7. Marcon, Andrea. Water cavitation peening for aerospace materials.

Degree: PhD, Mechanical Engineering, 2017, Georgia Tech

 Conventional shot peening has been used for almost a century as a means to mechanically improve the fatigue and corrosion resistance of metals. It employs… (more)

Subjects/Keywords: Peening; Cavitation; Fatigue

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APA (6th Edition):

Marcon, A. (2017). Water cavitation peening for aerospace materials. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59765

Chicago Manual of Style (16th Edition):

Marcon, Andrea. “Water cavitation peening for aerospace materials.” 2017. Doctoral Dissertation, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/59765.

MLA Handbook (7th Edition):

Marcon, Andrea. “Water cavitation peening for aerospace materials.” 2017. Web. 19 Mar 2019.

Vancouver:

Marcon A. Water cavitation peening for aerospace materials. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/59765.

Council of Science Editors:

Marcon A. Water cavitation peening for aerospace materials. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59765

8. Greer, Clayton M. Design of replacement structural components for fabrication using metal big area additive manufacturing.

Degree: MS, Mechanical Engineering, 2017, Georgia Tech

 Since the 1980s, additive manufacturing processes, commonly called 3D printing, have been used for prototyping applications due to low part strength. A new wire-feed metal… (more)

Subjects/Keywords: Additive manufacturing; Design for additive manufacturing

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APA (6th Edition):

Greer, C. M. (2017). Design of replacement structural components for fabrication using metal big area additive manufacturing. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58338

Chicago Manual of Style (16th Edition):

Greer, Clayton M. “Design of replacement structural components for fabrication using metal big area additive manufacturing.” 2017. Masters Thesis, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/58338.

MLA Handbook (7th Edition):

Greer, Clayton M. “Design of replacement structural components for fabrication using metal big area additive manufacturing.” 2017. Web. 19 Mar 2019.

Vancouver:

Greer CM. Design of replacement structural components for fabrication using metal big area additive manufacturing. [Internet] [Masters thesis]. Georgia Tech; 2017. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/58338.

Council of Science Editors:

Greer CM. Design of replacement structural components for fabrication using metal big area additive manufacturing. [Masters Thesis]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58338

9. Fergani, Omar. Materials-affected manufacturing in precision machining.

Degree: MS, Mechanical Engineering, 2014, Georgia Tech

 The influence of different microstructural attributes on the material properties such strength, hardness, residual stress or other physical properties are very well understood. During the… (more)

Subjects/Keywords: Machining; Residual stress; Microstructure

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APA (6th Edition):

Fergani, O. (2014). Materials-affected manufacturing in precision machining. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53103

Chicago Manual of Style (16th Edition):

Fergani, Omar. “Materials-affected manufacturing in precision machining.” 2014. Masters Thesis, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/53103.

MLA Handbook (7th Edition):

Fergani, Omar. “Materials-affected manufacturing in precision machining.” 2014. Web. 19 Mar 2019.

Vancouver:

Fergani O. Materials-affected manufacturing in precision machining. [Internet] [Masters thesis]. Georgia Tech; 2014. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/53103.

Council of Science Editors:

Fergani O. Materials-affected manufacturing in precision machining. [Masters Thesis]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53103

10. Liu, Ryan. Scalable machining of micro-features for orthopedic and tribological applications.

Degree: MS, Mechanical Engineering, 2016, Georgia Tech

 Micro-scale surface textures have found profound application in various industrial sectors, including the biomedical and tribological communities. While numerous manufacturing methods are available for the… (more)

Subjects/Keywords: Machining; Texturing; Manufacturing; Precision

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APA (6th Edition):

Liu, R. (2016). Scalable machining of micro-features for orthopedic and tribological applications. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58191

Chicago Manual of Style (16th Edition):

Liu, Ryan. “Scalable machining of micro-features for orthopedic and tribological applications.” 2016. Masters Thesis, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/58191.

MLA Handbook (7th Edition):

Liu, Ryan. “Scalable machining of micro-features for orthopedic and tribological applications.” 2016. Web. 19 Mar 2019.

Vancouver:

Liu R. Scalable machining of micro-features for orthopedic and tribological applications. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/58191.

Council of Science Editors:

Liu R. Scalable machining of micro-features for orthopedic and tribological applications. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/58191

11. Hahn, David Gil. Viscoelastic polymer-assisted mechanical exfoliation of large area highly oriented pyrolytic graphite.

Degree: MS, Mechanical Engineering, 2017, Georgia Tech

 There is a growing demand for a cost-effective, scalable, and reliable production method for 2D van der Waals materials such as graphene and pyrolytic graphite… (more)

Subjects/Keywords: Graphite; HOPG; PDMS; Mechanical exfoliation

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APA (6th Edition):

Hahn, D. G. (2017). Viscoelastic polymer-assisted mechanical exfoliation of large area highly oriented pyrolytic graphite. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58235

Chicago Manual of Style (16th Edition):

Hahn, David Gil. “Viscoelastic polymer-assisted mechanical exfoliation of large area highly oriented pyrolytic graphite.” 2017. Masters Thesis, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/58235.

MLA Handbook (7th Edition):

Hahn, David Gil. “Viscoelastic polymer-assisted mechanical exfoliation of large area highly oriented pyrolytic graphite.” 2017. Web. 19 Mar 2019.

Vancouver:

Hahn DG. Viscoelastic polymer-assisted mechanical exfoliation of large area highly oriented pyrolytic graphite. [Internet] [Masters thesis]. Georgia Tech; 2017. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/58235.

Council of Science Editors:

Hahn DG. Viscoelastic polymer-assisted mechanical exfoliation of large area highly oriented pyrolytic graphite. [Masters Thesis]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58235

12. Locks, Stephanie Isabel. General Bayesian approach for manufacturing equipment diagnostics using sensor fusion.

Degree: MS, Mechanical Engineering, 2016, Georgia Tech

 Statistical analysis is used quite heavily in production operations. To use certain advanced statistical approaches such as Bayesian analysis, statistical models must be built. This… (more)

Subjects/Keywords: Manufacturing; Bayesian; Naive Bayesian; Digital manufacturing

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APA (6th Edition):

Locks, S. I. (2016). General Bayesian approach for manufacturing equipment diagnostics using sensor fusion. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55036

Chicago Manual of Style (16th Edition):

Locks, Stephanie Isabel. “General Bayesian approach for manufacturing equipment diagnostics using sensor fusion.” 2016. Masters Thesis, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/55036.

MLA Handbook (7th Edition):

Locks, Stephanie Isabel. “General Bayesian approach for manufacturing equipment diagnostics using sensor fusion.” 2016. Web. 19 Mar 2019.

Vancouver:

Locks SI. General Bayesian approach for manufacturing equipment diagnostics using sensor fusion. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/55036.

Council of Science Editors:

Locks SI. General Bayesian approach for manufacturing equipment diagnostics using sensor fusion. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55036


Georgia Tech

13. Gorguluarslan, Recep Muhammet. A multi-level upscaling and validation framework for uncertainty quantification in additively manufactured lattice structures.

Degree: PhD, Mechanical Engineering, 2016, Georgia Tech

 Multiscale modeling techniques are playing an ever increasing role in the effective design of complex engineering systems including aircraft, automobiles, etc. Lightweight cellular lattice structures… (more)

Subjects/Keywords: Uncertainty quantification; Additive manufacturing; Cellular lattice structure; Validation

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APA (6th Edition):

Gorguluarslan, R. M. (2016). A multi-level upscaling and validation framework for uncertainty quantification in additively manufactured lattice structures. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56326

Chicago Manual of Style (16th Edition):

Gorguluarslan, Recep Muhammet. “A multi-level upscaling and validation framework for uncertainty quantification in additively manufactured lattice structures.” 2016. Doctoral Dissertation, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/56326.

MLA Handbook (7th Edition):

Gorguluarslan, Recep Muhammet. “A multi-level upscaling and validation framework for uncertainty quantification in additively manufactured lattice structures.” 2016. Web. 19 Mar 2019.

Vancouver:

Gorguluarslan RM. A multi-level upscaling and validation framework for uncertainty quantification in additively manufactured lattice structures. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/56326.

Council of Science Editors:

Gorguluarslan RM. A multi-level upscaling and validation framework for uncertainty quantification in additively manufactured lattice structures. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56326

14. Chen, Aoyu. Machine tool spindle bearing diagnostics under operating conditions.

Degree: PhD, Mechanical Engineering, 2017, Georgia Tech

 Bearing diagnostics provide valuable information related to a bearing’s health and facilitate Condition Based Maintenance (CBM) for rotary machines. This is an effective method to… (more)

Subjects/Keywords: Bearing diagnostics; Machine tool; Dynamic modeling; Defect size estimation

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APA (6th Edition):

Chen, A. (2017). Machine tool spindle bearing diagnostics under operating conditions. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58260

Chicago Manual of Style (16th Edition):

Chen, Aoyu. “Machine tool spindle bearing diagnostics under operating conditions.” 2017. Doctoral Dissertation, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/58260.

MLA Handbook (7th Edition):

Chen, Aoyu. “Machine tool spindle bearing diagnostics under operating conditions.” 2017. Web. 19 Mar 2019.

Vancouver:

Chen A. Machine tool spindle bearing diagnostics under operating conditions. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/58260.

Council of Science Editors:

Chen A. Machine tool spindle bearing diagnostics under operating conditions. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58260

15. Zeng, Zhi. Multiscale modeling and uncertainty analysis of mechanical behavior of nanostructural metals.

Degree: PhD, Mechanical Engineering, 2017, Georgia Tech

 Metals with heterogeneous nanostructures hold great promise for achieving a synergy of ultra-high strength and ductility, thus overcoming the conventional strength-ductility tradeoff in nanostructured materials.… (more)

Subjects/Keywords: Heterogeneous nanostructured metals; Molecular dynamics; Crystal plasticity finite element; Uncertainty quantification

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APA (6th Edition):

Zeng, Z. (2017). Multiscale modeling and uncertainty analysis of mechanical behavior of nanostructural metals. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58239

Chicago Manual of Style (16th Edition):

Zeng, Zhi. “Multiscale modeling and uncertainty analysis of mechanical behavior of nanostructural metals.” 2017. Doctoral Dissertation, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/58239.

MLA Handbook (7th Edition):

Zeng, Zhi. “Multiscale modeling and uncertainty analysis of mechanical behavior of nanostructural metals.” 2017. Web. 19 Mar 2019.

Vancouver:

Zeng Z. Multiscale modeling and uncertainty analysis of mechanical behavior of nanostructural metals. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/58239.

Council of Science Editors:

Zeng Z. Multiscale modeling and uncertainty analysis of mechanical behavior of nanostructural metals. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58239

16. Fernandez-Zelaia, Patxi. Quantitative methods for inferring process-structure-property relations in machining.

Degree: PhD, Mechanical Engineering, 2018, Georgia Tech

 Metal machining subjects material to large strains (e > 1) at extremely high rates (rate > 1000 s-1) while simultaneously imposing heating due to dissipated… (more)

Subjects/Keywords: Machining; Severe plastic deformation; Materials informatics; Applied statistics

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APA (6th Edition):

Fernandez-Zelaia, P. (2018). Quantitative methods for inferring process-structure-property relations in machining. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60803

Chicago Manual of Style (16th Edition):

Fernandez-Zelaia, Patxi. “Quantitative methods for inferring process-structure-property relations in machining.” 2018. Doctoral Dissertation, Georgia Tech. Accessed March 19, 2019. http://hdl.handle.net/1853/60803.

MLA Handbook (7th Edition):

Fernandez-Zelaia, Patxi. “Quantitative methods for inferring process-structure-property relations in machining.” 2018. Web. 19 Mar 2019.

Vancouver:

Fernandez-Zelaia P. Quantitative methods for inferring process-structure-property relations in machining. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/1853/60803.

Council of Science Editors:

Fernandez-Zelaia P. Quantitative methods for inferring process-structure-property relations in machining. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60803

.