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Reproducibility Dataset for "Defect-Aware Thermoforming of Continuous-Fiber Thermoplastic Composites: A Physics-Guided Bayesian Decision Layer for Resource-Aware Process-Window Discovery"

Year: 2026

Type: dataset

Abstract: This dataset supports the manuscript “Defect-Aware Thermoforming of Continuous-Fiber Thermoplastic Composites: A Physics-Guided Bayesian Decision Layer for Resource-Aware Process-Window Discovery.” The primary dataset contains a 4,000-design physics-guided emulation benchmark comprising 1,000 Latin-hypercube candidate designs at each of four forming times (1.6, 3.2, 4.8, and 6.4 s). The emulation responses are not direct extractions of the archived FE VTK fields.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.22819985

Authors: Barah, Obinna Onyebuchi, Otaru, Abdulrazak Jinadu, Bori, Ige, Al-Yaari, Mohammed

Institutions: Kampala International University, King Faisal University, Federal University of Technology Minna

Language: English

Topic: Advanced Multi-Objective Optimization Algorithms

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7213526366

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