2026-09-19T02:39:11Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/129346 2025-10-20 col_2142_5131 col_2142_14800 com_2142_5130 com_2142_14799 com_2142_234

application/pdf en text Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms The student, Abhishek Iyer, accepted the attached license on 2025-05-08 at 18:08. The student, Abhishek Iyer, submitted this Thesis for approval on 2025-05-08 at 18:13. This Thesis was approved for publication on 2025-05-09 at 12:15. DSpace SAF Submission Ingestion Package generated from Vireo submission #22271 on 2025-10-19 at 18:13:57 KL divergence – based disagreement sampling for multi-fidelity Bayesian optimization Iyer, Abhishek 2025-05-09 Smart, Jordan Active Learning Bayesian Optimization Multi-fidelity Airfoil eng Computational costs have increased tremendously over time owing to the increase in complexity of design. The motivation to reduce costs has led to the adoption of multi-fidelity optimization techniques. Active Learning has gained prominence as a sampling method which allows for maximum optimization of the design problem while utilizing minimal available data, consequently decreasing the cost of computation. This thesis proposes a novel KL-Divergence sampling strategy which iteratively makes use of fidelities to sample through a design space to optimize according to a target objective. This method was evaluated using the Rastrigin function and then applied on a design space consisting of 4-digit NACA airfoil combinations. It is observed that the KL divergence method provided a better optimization result compared to the Least Confidence method while simultaneously reducing reliance on information from higher fidelities. The disagreement sampler iterated over the airfoil design space and provided a better result as compared to the Least Confidence method. 2025-05 Text https://hdl.handle.net/2142/129346 Copyright 2025 Abhishek Iyer Aerospace Engineering Aerospace Engineering University of Illinois Urbana-Champaign M.S. Thesis