Physics-informed Gaussian process classification for constraint-aware alloy design Article Swipe

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Cliff Hardcastle , Ryan O'Mullan , Raymundo Arróyave , Brent Vela ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1039/d5dd00084j

Alloy design can be framed as a constraint-satisfaction problem. Building on previous methodologies, we propose equipping Gaussian Process Classifiers (GPCs) with physics-informed prior mean functions to model the centers of feasible design spaces.

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Mechanical Engineering

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Gaussian process Constraint (computer-aided design) Alloy Process (computing) Gaussian Computer science Statistical physics Materials science Physics Mechanical engineering Engineering Metallurgy Programming language Quantum mechanics

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Type: article
Language: en
Landing Page: https://doi.org/10.1039/d5dd00084j
PDF: https://pubs.rsc.org/en/content/articlepdf/2025/dd/d5dd00084j
OA Status: diamond
Cited By: 2
References: 37
Related Works: 10
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DOI: https://doi.org/10.1039/d5dd00084j

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Title: Physics-informed Gaussian process classification for constraint-aware alloy design

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Language: en

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Publication year: 2025

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Publication date: 2025-01-01

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Authors: Cliff Hardcastle, Ryan O'Mullan, Raymundo Arróyave, Brent Vela

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Landing page: https://doi.org/10.1039/d5dd00084j

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Concepts: Gaussian process, Constraint (computer-aided design), Alloy, Process (computing), Gaussian, Computer science, Statistical physics, Materials science, Physics, Mechanical engineering, Engineering, Metallurgy, Programming language, Quantum mechanics

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Cited by: 2

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