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Edgar Galvan
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Journal Articles

Computational Design of Gradient Paths in Additively Manufactured Functionally Graded Materials

Tanner Kirk, Edgar Galvan, Richard Malak, Raymundo Arroyave
Journal: Journal of Mechanical Design
Article Type: Research-Article
J. Mech. Des. November 2018, 140(11): 111410.
Paper No: MD-18-1274
DOI: https://doi.org/10.1115/1.4040816
Published Online: September 7, 2018
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Topics: Additive manufacturing, Algorithms, Design, Functionally graded materials, Path planning, Temperature, Manufacturing
Proceedings Papers

Design Optimization of Folding Solar Powered Autonomous Underwater Vehicles Using Origami Architecture

Doe Young Hur, Edwin Peraza Hernandez, Edgar Galvan, Darren Hartl, Richard Malak
Proc. ASME. IDETC-CIE2017, Volume 5B: 41st Mechanisms and Robotics Conference, V05BT08A048, August 6–9, 2017
Paper No: DETC2017-67848
DOI: https://doi.org/10.1115/DETC2017-67848
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Topics: Design, Optimization, Solar power, Underwater vehicles, Shapes, Computational fluid dynamics, Dimensions, Solar energy, Active materials, Actuators
Journal Articles

A Constraint Satisfaction Algorithm for the Generalized Inverse Phase Stability Problem

Edgar Galvan, Richard J. Malak, Sean Gibbons, Raymundo Arroyave
Journal: Journal of Mechanical Design
Article Type: Research-Article
J. Mech. Des. January 2017, 139(1): 011401.
Paper No: MD-16-1227
DOI: https://doi.org/10.1115/1.4034581
Published Online: October 5, 2016
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Topics: Algorithms, Stability, Design
Journal Articles

Parameterized Design Optimization of a Magnetohydrodynamic Liquid Metal Active Cooling Concept

Darren J. Hartl, Edgar Galvan, Richard J. Malak, Jeffrey W. Baur
Journal: Journal of Mechanical Design
Article Type: Research-Article
J. Mech. Des. March 2016, 138(3): 031402.
Paper No: MD-15-1479
DOI: https://doi.org/10.1115/1.4032268
Published Online: January 18, 2016
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Topics: Design, Magnetohydrodynamics, Optimization, Cooling, Algebra
Proceedings Papers

Constraint Satisfaction Approach to the Design of Multi-Component, Multi-Phase Alloys

Edgar Galvan, Richard J. Malak, Jr., Sean Gibbons, Raymundo Arroyave
Proc. ASME. IDETC-CIE2014, Volume 2B: 40th Design Automation Conference, V02BT03A010, August 17–20, 2014
Paper No: DETC2014-34707
DOI: https://doi.org/10.1115/DETC2014-34707
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Topics: Alloys, Design, Algorithms, Databases, Stability, Encryption, Equilibrium (Physics), Errors, Evolutionary computation, Inverse problems
Journal Articles

P3GA: An Algorithm for Technology Characterization

Edgar Galvan, Richard J. Malak
Journal: Journal of Mechanical Design
Article Type: Research-Article
J. Mech. Des. January 2015, 137(1): 011401.
Paper No: MD-13-1114
DOI: https://doi.org/10.1115/1.4028101
Published Online: January 1, 2015
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Topics: Algorithms, Approximation, Design, Engineering disciplines, Engineers, Preferences, Genetic algorithms, Systems engineers
Journal Articles

Technology Characterization Models and Their Use in Systems Design

Robert R. Parker, Edgar Galvan, Richard J. Malak
Journal: Journal of Mechanical Design
Article Type: Research-Article
J. Mech. Des. July 2014, 136(7): 071003.
Paper No: MD-12-1155
DOI: https://doi.org/10.1115/1.4025960
Published Online: April 28, 2014
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Topics: Design, Interpolation, Heat exchangers, Optimization, Engineering disciplines
Journal Articles

Design and Optimization of a Shape Memory Alloy-Based Self-Folding Sheet

Edwin Peraza-Hernandez, Darren Hartl, Edgar Galvan, Richard Malak
Journal: Journal of Mechanical Design
Article Type: Research-Article
J. Mech. Des. November 2013, 135(11): 111007.
Paper No: MD-13-1078
DOI: https://doi.org/10.1115/1.4025382
Published Online: October 3, 2013
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Topics: Design, Wire, Optimization, Elastomers, Temperature, Stress, Materials properties, Constitutive equations
Proceedings Papers

A Genetic Algorithm Approach for Technology Characterization

Edgar Galvan, Richard Malak
Proc. ASME. IDETC-CIE2012, Volume 3: 38th Design Automation Conference, Parts A and B, 777-788, August 12–15, 2012
Paper No: DETC2012-70465
DOI: https://doi.org/10.1115/DETC2012-70465
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Topics: Algorithms, Decision making, Design, Engineers, Genetic algorithms, Machine learning, Modeling, Optimization